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arXiv 2022年

作者： Zhu, Dafeng Yang, Bo Ma, Chengbin Wang, Zhaojian Zhu, Shanying Ma, Kai Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China

Contemporary industrial parks are challenged by the growing concerns about high cost and low efficiency of energy supply. Moreover, in the case of uncertain supply/demand, how to mobilize delay-tolerant elastic loads and compensate real-time inelastic loads to match multi-energy generation/storage and minimize energy cost is a key issue. Since energy management is hardly to be implemented offline without knowing statistical information of random variables, this paper presents a systematic online energy cost minimization framework to fulfill the complementary utilization of multi-energy with time-varying generation, demand and price. Specifically to achieve charging/discharging constraints due to storage and short-term energy balancing, a fast distributed algorithm based on stochastic gradient with two-timescale implementation is proposed to ensure online implementation. To reduce the peak loads, an incentive mechanism is implemented by estimating users' willingness to shift. Analytical results on parameter setting are also given to guarantee feasibility and optimality of the proposed design. Numerical results show that when the bid-ask spread of electricity is small enough, the proposed algorithm can achieve the close-to-optimal cost asymptotically. © 2022, CC BY-NC-ND.

关键词： Energy management

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Analysis of anesthesia depth based on electroencephalogram

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Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) 2011年第SUPPL. 1期42卷 712-716页

作者： Zhang, Xue-Yan Zhao, Li-Mei Yang, Sheng-Gang Department of Information Technology Ningbo Radio and TV University Ningbo 315020 China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

To find a useful index for real-time monitoring of anesthesia depth by analysing time-frequency balanced spectral entropy(TBSE) and permutation entropy(PE) of electroencephalogram (EEG). EEG signals of patients during general anesthesia were randomly chosen and recorded as the subjects. The TBSEs of EEG corresponding to different depths of anesthesia were studied and the relationship between TBSE and the depths of anesthesia were analysed. The results show that while the depth of anesthesia increases the TBSE of EEG will decrease. TBSE can be applied to detect the depth of anesthesia sensitively. The algorithm of PE is highly resistant to strong transient interference, so it can be used as a practical index for on line monitoring of the depth of anesthesia in clinical practice.

关键词： Electroencephalography

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Cooperative and Active Sensing in Mobile Sensor Networks for Scalar Field Mapping

Cooperative and Active Sensing in Mobile Sensor Networks for...

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IEEE International Conference on Automation Science and engineering

作者： Hung Manh La Weihua Sheng Jiming Chen Center for Advanced Infrastructure and Transportation (CAIT) Rutgers University Piscataway NJ 08854 USA School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078 USA State Key Lab. of Industrial Control Technology Department of Control Zhejiang University Hangzhou P.R.China 310027

ISBN: (纸本)9781479915132

Scalar field mapping has many applications including environmental monitoring, search and rescue, etc. In such applications there is a need to achieve a certain level of confidence regarding the estimates at each location. In this paper, a cooperative and active sensing framework is developed to enable scalar field mapping using multiple mobile sensor nodes. The cooperative and active controller is designed via the real-time feedback of the sensing performance to steer the mobile sensors to new locations in order to improve the sensing quality. During the movement of the mobile sensors, the measurements from each sensor node and its neighbors are taken and fused with the corresponding confidences using distributed consensus filters. As a result an online map of the scalar field is built with a certain level of confidence of the estimates. We conducted computer simulations to validate and evaluate our proposed algorithms

关键词： Active sensing Sensor fusion Sensor networks

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Performance-aware power management in embedded controllers with multiple-voltage processors

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Information Technology Journal 2008年第6期7卷 942-947页

作者： Xia, Feng Liu, Liping Ma, Longhua Sun, Youxian Dong, Jinxiang College of Computer Science and Technology Zhejiang University Hangzhou 310027 China School of Electrical Engineering and Automation Tianjin University Tianjin 300072 China State Key Lab of Industrial Control Technology Zhejiang University Hangzhou 310027 China Faculty of Information Technology Queensland University of Technology Brisbane QLD 4001 Australia

The aim of this research is to minimize the energy dissipation of embedded controllers without jeopardizing the Quality of control (QoC). Taking advantage of the Dynamic Voltage Scaling (DVS) technology, this study develops a performance-aware power management scheme for embedded controllers with processors that allow multiple voltage levels. The periods of control tasks are adapted online with respect to the current QoC, thus facilitating additional energy reduction over standard DVS. To avoid the waste of CPU resources as a result of the discrete voltage levels, a resource reclaiming mechanism is employed to maximize the CPU utilization and also to improve the QoC Simulations are conducted to evaluate the performance of the proposed scheme. Compared with the optimal standard DVS scheme, the proposed scheme is shown to be able to save remarkably more energy while maintaining comparable QoC. © 2008 Asian Network for Scientific Information.

关键词： Real time control

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Biocompatible chitosan/polyethylene glycol/multi-walled carbon nanotube composite scaffolds for neural tissue engineering

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2022年第1期23卷 58-73页

作者： Shengbo SANG Rong CHENG Yanyan CAO Yayun YAN Zhizhong SHEN Yajing ZHAO Yanqing HAN Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Information and ComputerTaiyuan University of TechnologyTaiyuan030024China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan030024China College of Information Science and Engineering Hebei North UniversityZhangjiakou075000China Shanxi Six-Dimensional Artificial Intelligence Biomedical Research Institute Taiyuan030031China Department of Neurology Shanxi Provincial Cardiovascular HospitalTaiyuan030024China

Carbon nanotube(CNT)composite materials are very attractive for use in neural tissue engineering and biosensor *** scaffolds are excellent mimics of extracellular matrix due to their hydrophilicity,viscosity,and *** can also impart conductivity to other insulating materials improve mechanical stability guide neuronal cell behavior and trigger axon *** performance of chitosan(CS)/polyethylene glycol(PEG)composite scaffolds could be optimized by introducing multi-walled CNTs(MWCNTs).CS/PEG/CNT composite scaffolds with CNT content of 1%,3%,and 5%(1%=0.01 g/mL)were prepared by *** physical and chemical properties and biocompatibility were *** electron microscopy(SEM)showed that the composite scaffolds had a highly connected porous *** electron microscope(TEM)and Raman spectroscopy proved that the CNTs were well dispersed in the CS/PEG matrix and combined with the CS/PEG nanofiber *** enhanced the elastic modulus of the *** porosity of the scaffolds ranged from 83%to 96%.They reached a stable water swelling state within 24 h,and swelling decreased with increasing MWCNT *** electrical conductivity and cell adhesion rate of the scaffolds increased with increasing MWCNT *** showed that rat pheochromocytoma(PC12)cells grown in the scaffolds had characteristics similar to nerve *** measured changes in the expression of nerve cell markers by quantitative real-time polymerase chain reaction(qRT-PCR),and found that PC12 cells cultured in the scaffolds expressed growth-associated protein 43(GAP43),nerve growth factor receptor(NGFR),and class IIIβ-tubulin(TUBB3)*** research showed that the prepared CS/PEG/CNT scaffold has good biocompatibility and can be further applied to neural tissue engineering research.

关键词： Multi-walled carbon nanotube(MWCNT) Cell-scaffold PC12 cells Biocompatibility

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Corrigendum to “Development and investigation of efficient artificial bee colony algorithm for numerical function optimization” [Appl. Soft Comput. 12 (2012) 320–332]

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Applied Soft Computing 2013年第4期13卷 2143-2143页

作者： Guoqiang Li Peifeng Niu Xingjun Xiao Institute of Electrical Engineering Yanshan University Qinhuangdao 066004 China Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

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ERT-GFAN: A multimodal drug–target interaction prediction model based on molecular biology and knowledge-enhanced attention mechanism

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computers in Biology and Medicine 2024年 180卷 109012-109012页

作者： Cheng, Xiaoqing Yang, Xixin Guan, Yuanlin Feng, Yihan College of Computer Science and Technology Qingdao University Qingdao266071 China School of Automation Qingdao University Qingdao266071 China School of Mechanical and Automotive Engineering Qingdao University of Technology Qingdao266071 China Key Lab of Industrial Fluid Energy Conservation and Pollution Control Ministry of Education Qingdao University of Technology Qingdao266071 China

In drug discovery, precisely identifying drug–target interactions is crucial for finding new drugs and understanding drug mechanisms. Evolving drug/target heterogeneous data presents challenges in obtaining multimodal representation in drug–target prediction(DTI). To deal with this, we propose ‘ERT-GFAN’, a multimodal drug–target interaction prediction model inspired by molecular biology. Firstly, it integrates bio-inspired principles to obtain structure feature of drugs and targets using Extended Connectivity Fingerprints(ECFP). Simultaneously, the knowledge graph embedding model RotatE is employed to discover the interaction feature of drug–target pairs. Subsequently, Transformer is utilized to refine the contextual neighborhood features from the obtained structure feature and interaction features, and multi-modal high-dimensional fusion features of the three-modal information constructed. Finally, the final DTI prediction results are outputted by integrating the multimodal fusion features into a graphical high-dimensional fusion feature attention network (GFAN) using our innovative multimodal high-dimensional fusion feature attention. This multimodal approach offers a comprehensive understanding of drug–target interactions, addressing challenges in complex knowledge graphs. By combining structure feature, interaction feature, and contextual neighborhood features, ‘ERT-GFAN’ excels in predicting DTI. Empirical evaluations on three datasets demonstrate our method's superior performance, with AUC of 0.9739, 0.9862, and 0.9667, AUPR of 0.9598, 0.9789, and 0.9750, and Mean Reciprocal Rank(MRR) of 0.7386, 0.7035, and 0.7133. Ablation studies show over a 5% improvement in predictive performance compared to baseline unimodal and bimodal models. These results, along with detailed case studies, highlight the efficacy and robustness of our approach. © 2024 Elsevier Ltd

关键词： Forecasting

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Self-Induced Backaction Optical Pulling Force

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Physical Review Letters 2018年第12期120卷 123901-123901页

作者： Tongtong Zhu Yongyin Cao Lin Wang Zhongquan Nie Tun Cao Fangkui Sun Zehui Jiang Manuel Nieto-Vesperinas Yongmin Liu Cheng-Wei Qiu Weiqiang Ding Department of Physics Harbin Institute of Technology Harbin 150001 China Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117583 Singapore Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan 030024 China Department of Biomedical Engineering Dalian University of Technology Dalian 116024 China Instituto de Ciencia de Materiales de Madrid Consejo Superior de Investigaciones Científicas Campus de Cantoblanco Madrid 28049 Spain Departments of Mechanical and Industrial Engineering and Electrical and Computer Engineering Northeastern University Boston Massachusetts 02115 USA

We achieve long-range and continuous optical pulling in a periodic photonic crystal background, which supports a unique Bloch mode with the self-collimation effect. Most interestingly, the pulling force reported here is mainly contributed by the intensity gradient force originating from the self-induced backaction of the object to the self-collimation mode. This force is sharply distinguished from the widely held conception of optical tractor beams based on the scattering force. Also, this pulling force is insensitive to the angle of incidence and can pull multiple objects simultaneously.

关键词： Electromagnetism Mechanical effects of light on material media Photonic crystals Optical microcavities Optical tweezers

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虚拟手术中基于凸多边形的软组织切割算法研究

虚拟手术中基于凸多边形的软组织切割算法研究

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第十二届中国虚拟现实大会

作者： WANG Hong-rui 王洪瑞 CHEN Li-min 陈利敏 ZHAO Bing 赵冰 WANG Hong-bin 王洪斌 Key Lab of Industrial Computer Control Engineering of Hebei Province in Yanshan University Qinhuang 燕山大学工业计算机控制工程河北省重点实验室秦皇岛 066004

虚拟手术仿真系统为医学教学提供了一种方便、廉价、有效的方法。切割模拟是该系统重要组成部分，影响整个系统的实时性和真实性，因此对整个切割过程进行深入研究并提出了基于凸多边形的切割算法。首先通过遍历优化索引结构后的八叉树... 详细信息

虚拟手术仿真系统为医学教学提供了一种方便、廉价、有效的方法。切割模拟是该系统重要组成部分，影响整个系统的实时性和真实性，因此对整个切割过程进行深入研究并提出了基于凸多边形的切割算法。首先通过遍历优化索引结构后的八叉树来寻找切割起点，由起点开始，以切割轨迹为参照，采用邻居搜索策略寻找所有被切割的三角影，然后通过引入辅助单元组成凸多边形，再对凸多边形进行三角剖分，以实现网格重构。实验证明新的剖分算法抑制了模型单元数量的急剧增长，提高了三角形重构的质量。

关键词：虚拟手术仿真系统软组织切割算法凸多边形网格模型

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Improved ECO Algorithm Based on Residual Neural Network

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Journal of Physics: Conference Series 2021年第1期1732卷

作者： Huifang Qi Changmeng Wang Bo Li School of Information Science and Engineering Yanshan University Qinhuangdao China School of Electrical Engineering Yanshan University Qinhuangdao China Key Laboratory of industrial computer control engineering in Hebei Province Yanshan University Qinhuangdao China

Video target tracking is one of hot fields of computer vision, and its application is also very extensive. However, due to the complexity and variability of tracking environment, which brings some challenges to the research of target tracking. ECO(Efficient Convolution Operators) Algorithm is proposed based on convolutional neural network in three aspects. Firstly, residual neural network ResNet50 is adopted instead of convolutional neural network to extract the appearance features of target, and deeper residual neural network is applied to obtain more abundant target semantic information, so as to improve the tracking effect of tracking ***, sample space classification strategy is improved. Different weights are assigned to shallow feature and deep feature, which make the deep feature play a more important role and improve the effect of target tracking. Finally, the method of scale estimation is improved so that better bounding boxes can be estimated with the scale changing. Experimental results show that the distance accuracy and success rate of the algorithm.

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