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2022 4th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2022

作者： Qian, Quan Zhu, Yuan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Medication design and repositioning are sped up by the prediction of drug-target interactions (DTIs). Two main kinds of prediction methods are commonly used, which are based on chemical structure feature extraction and deep learning methods. However, on the one hand, the DTI prediction approaches based on chemical structural feature extraction may not wholly explore the possible network characteristics in the data. On the other hand, many deep learning methods call for numerous layers of neural networks to be layered to learn higher-order feature interaction information. To sum up, the existing computation methods often have the limitations of gradient disappearance and overfitting. This study presents a novel method (JRD-NFM) by calculating Jaccard similarities, getting an eigenvector through Restarted random walk (RWR), and generating low-dimensional feature vectors by Disposition Component Analysis (DCA). Besides decoding the topological features and similarity information of target and drug node, it can also get the context information of a single network. Considering the advantages of Neural Factorization Machines (NFM) in extracting high-order nonlinear features and processing sparse data, this study use NFM to classifier the collection data to integrate drug and target biochemical structure information. The experimental results demonstrate that JRD-NFM can outperform widely used deep learning methods and conventional chemical structure approaches. It could provide fresh ideas for combining molecular structure and heterogeneous network data to predict DTIs. © Published under licence by IOP Publishing Ltd.

关键词： Feature extraction

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Correction of Images Projected on Non-White Surfaces Based on Deep Neural Network 14

Correction of Images Projected on Non-White Surfaces Based o...

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14th International Conference on Digital Image processing, ICDIP 2022

作者： Wang, Zewei Zhang, Jingjing Du, Xingzhuo Cao, Sihua Wei, Wenxuan School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

ISBN: (纸本)9781510657564

When projecting onto a non-white surface, the projected image is distorted or color mixing by complex luminance and chrominance information, which makes the projection result different from the visual perception of the human eye. The purpose of projection image correction is to remove these effects, and traditional solutions usually estimate parameters from the collected projection samples, compute an inverse model of the projection imaging process, and try to fit a correction function. In this paper, a deep neural network-based projection image correction network (PICN) is designed to implicitly learn complex correction functions. PICN consists of a U-shaped backbone network, a convolutional neural network that extracts projected surface features, and a perceptual loss network that optimizes the correction results. Such a structure can not only extract the deep features and surface interference features of the projected image, but also make the corrected projected image more in line with human visual perception. In addition, we built a projector-camera system under the condition of a fixed global illumination environment for verification experiment, and proved the effectiveness of the proposed method by calculating the evaluation metrics of projected images before and after correction. © 2022 SPIE.

关键词： Deep neural networks

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KNTU-RoboGlove: Design of a Pneumatic Soft Robotic Glove 11

KNTU-RoboGlove: Design of a Pneumatic Soft Robotic Glove

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Boka, Tanin Nikkhah, M. Navid Moosavian, S. Ali A. Toosi University of Technology Tehran Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems Laboratory Dept of Mechanical Engineering K. N. Tehran Iran K. N. Toosi University of Technology Tehran Dept of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798350308105

This paper introduces an innovative advancement in the field of wearable assistive technology by presenting a revolutionary portable soft robotic glove designed to assist individuals with hand impairments during rehabilitation exercises and daily tasks. The glove offers both active finger flexion and passive extension to aid in hand support and rehabilitative training. It achieves this by utilizing integrated soft actuators, including a variable stiffness layer and a pneumatic-driven layer, which guide specific bending, twisting, and extending movements when air pressure is applied. Notably, the variable stiffness layer takes inspiration from pangolins, whose scales are pliable during daily activities but become rigid when facing threats. To provide increased power with enhanced stiffness, a toothed pneumatic actuator is specially designed. The three-finger soft glove is manufactured by molding super-elastic material, creating the actuator mold using a 3D printer. The glove's grasping abilities have been thoroughly tested, and experimental results demonstrate that, when compared to previously developed elastomeric-based actuators, these actuators can generate substantial force and torque to facilitate finger flexion even at lower air pressure levels. This capability allows the glove to grasp a wide range of objects, assisting individuals in their rehabilitative training. Furthermore, a control system for grasping has been developed, which includes motion processing unit sensors for collecting feedback signals aligned with the actuators, along with a closed-loop controller for regulating the pressure. In contrast to existing devices, this glove, thanks to its portable design, has the potential to significantly enhance user autonomy and independence. © 2023 IEEE.

关键词： Pneumatic actuators

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Design of Load Frequency controller for Power System Based on Equivalent Input Disturbance Method

Design of Load Frequency Controller for Power System Based o...

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New Energy and Energy Storage System control Summit Forum (NEESSC)

作者： Jianrong Zhang Hang Xu Hongzhang Wang Chuanke Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798350389012

ISBN: (纸本)9798350389029

In the power system, due to the instability of the external environment, safe and stable operation cannot always be guaranteed, as it frequently encounters varying degrees of external disturbances. In order to mitigate the effects of these disturbances on the system, the power system can operate safely and stably, In this paper, a power system load frequency control (LFC) based on Equivalent Input Disturbance (EID) method is proposed from the perspective of active disturbance suppression. Firstly, the disturbances present in the environment are unified as external disturbances, and then a single area the electric power system model with external disturbance was constructed. Then, a controller algorithm based on EID was designed using EID equivalent processing method and linear matrix inequality method to address the issue of external interference in the power system. Finally, a numerical example is used to validate the effectiveness and accuracy of the controller by simulating with two aspects, fixed perturbation and random perturbation, respectively.

关键词： Perturbation methods Process control Interference Power system stability control systems Linear matrix inequalities Numerical models Frequency control Load modeling Energy storage

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Norm-Integrated Softmax Loss For Deep Face Recognition

Norm-Integrated Softmax Loss For Deep Face Recognition

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IEEE International Conference on Image processing

作者： Jun Chen Yiwei Wang Haiyan Zhang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

The key to face recognition lies in how to improve the model’s ability to extract facial features. To this end, numerous loss functions based on different metrics have been proposed to increase the margin of feature distinction between different classes. Methods based on Cosine distance significantly enhance face recognition performance by focusing on angular constraints between samples and classes, demonstrating their superiority over those based on Euclidean distance. However, a significant oversight in these methods is the neglect of feature magnitude’s importance in representing facial features. To address this gap, our study introduces the NormIntegrated Softmax loss (NIface loss), a novel loss function that amalgamates feature norms with angular information. This integration offers a comprehensive perspective for feature classification, augmenting the compactness of intra-class features. Extensive evaluations on large-scale public datasets have demonstrated the efficacy of NIface loss in enhancing recognition accuracy and stability.

关键词： Measurement Technological innovation Image recognition Accuracy Face recognition Focusing Euclidean distance

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Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 957-968页

作者： Jinhua She Kou Miyamoto Qing-Long Han Min Wu Hiroshi Hashimoto Qing-Guo Wang School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan K.Miyamoto is with the Institute of Technology Shimizu CorporationKotoTokyo 135-0044Japan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China School of Industrial Technology Advanced Institute of Industrial TechnologyTokyo 140-0011Japan Institute of Artificial Intelligence and Future Networks Beijing Normal UniversityZhuhai 519087 Guangdong Key Lab of AI and Multi-Modal Data Processing Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNUHKBU United International College Zhuhai 519087China

Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state *** paper presents a deep observation on and a comparison between two of those methods:the generalized extended-state observer(GESO)and the equivalent input disturbance(EID)from assumptions,system configurations,stability conditions,system design,disturbance-rejection performance,and extensibility.A time-domain index is introduced to assess the disturbance-rejection performance.A detailed observation of disturbance-suppression mechanisms reveals the superiority of the EID approach over the GESO method.A comparison between these two methods shows that assumptions on disturbances are more practical and the adjustment of disturbance-rejection performance is easier for the EID approach than for the GESO method.

关键词： Active disturbance-rejection control(ADRC) disturbance observer(DOB) equivalent input disturbance(EID) extendedstate observer(ESO) generalized extended-state observer(GESO)

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Development prospects of metal-based two-dimensional nanomaterials in lithium-sulfur batteries

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Chinese Chemical Letters 2023年第1期34卷 102-113页

作者： Yuxue Mo Liling Liao Dongyang Li Rongwu Pan Yanhong Deng Yanliang Tan Haiqing Zhou College of Physics and Electronic Engineering Hengyang Normal UniversityHengyang 421002China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Key Laboratory for Matter Microstructure and Function of Hunan ProvinceDepartment of Physics and Synergetic Innovation Center for Quantum Effects and ApplicationsHunan Normal UniversityChangsha 410081China Hunan Joint International Laboratory of Advanced Materials and Technology for Clean Energy Changsha 410082China Hunan Shengli High-tech Energy Technology Co. Ltd.Yongzhou 425000China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang 421002China

A lithium-sulfur(Li-S)system is an important candidate for future lithium-ion system due to its low cost and high specific theoretical capacity(1675 m Ah/g,2600 Wh/kg),which is greatly hindered by the poor conductivity of sulfur,large volume change and dissolution of lithium ***-dimensional(2D)materials with monolayers or few-layers usually have peculiar structures and physical/chemical properties,which can resolve the critical issues in Li-S ***,the metal-based 2D nanomaterials,including ferrum,cobalt or other metal-based composites with various anions,can provide high conductivity,large surface area and abundant reaction sites for restraining the diffusion for lithium *** this mini-review,we will present an overview of recent developments on metal-based 2D nanomaterials with various anions as the electrode materials for Li-S *** the main bottleneck for the Li-S system is the shuttle of polysulfides,emphasis is placed on the structure and components,physical/chemical interaction and interaction mechanisms of the 2D ***,the challenges and prospects of metal-based 2D nanomaterials for Li-S batteries are discussed and proposed.

关键词： Lithium-sulfur battery Two-dimensional materials Cathode materials Anode materials Anode protection

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Fabrication and Path Following control of a Magnetic Soft Microrobot 8

Fabrication and Path Following Control of a Magnetic Soft Mi...

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8th International Conference on control Science and systems Engineering, ICCSSE 2022

作者： Tang, Jianhui Zhang, Pan Wu, Jundong Wang, Yawu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665484138

Magnetically-controlled soft microrobots have great application prospects because of small size, flexible motion and wireless control. In this paper, a magnetically-controlled soft microrobot is designed and fabricated. In order to achieve its path-following control, two open-loop control strategies and a closed-loop one are developed. Especially, for the closed-loop control strategy, we present the image processing method and the pure pursuit algorithm, where the former is used to obtain the position and posture of the microrobot required for the latter. Finally, the developed open-loop and closed-loop control strategies are verified by carrying out the experiments. These methods are promising in numerous applications because of the ease of implementation. © 2022 IEEE.

关键词： Image processing

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Oilwell Downhole RFID Reader based on Discrete Components

Oilwell Downhole RFID Reader based on Discrete Components

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2021 International Conference on Signal processing and Communication Technology, SPCT 2021

作者： Liu, Xiaokun Zhu, Jixuan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (数字)9781510653344

ISBN: (纸本)9781510653337

RFID (Radio Frequency Identification) is expected to provide a new way for the efficient and low-cost control of oilwell downhole tools, and bring huge economic benefits. However, the RF (radio frequency) base station chips on the market could not withstand the high temperature of downhole. In this paper, discrete components are used to build RF front-end circuits to realize the drive and demodulation functions of RF base station chips. The circuit parameters are adjusted and optimized through circuit simulation. Then, the software and hardware design of the downhole reader are accomplished. Finally, experimental results show that the proposed downhole reader based on discrete components can successfully demodulate and read the tag data. © 2022 SPIE.

关键词： Circuit simulation

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