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Predicting Cell Line-Specific Synergistic Drug Combinations Through Siamese Network with Attention Mechanism 1

2nd International Conference on Cognitive Computation and Systems, ICCCS 2023

作者： Bao, Xin Chen, XiangYong Qiu, JianLong Wang, Donglin Qian, Xuewu Sun, JianQiang School of Information Science and Engineering Linyi University Linyi276005 China School of Automation and Electrical Engineering Linyi University Linyi276005 China Jinan Key Laboratory of 5G+ Advanced Control Technology Jinan250103 China

ISBN: (数字)9789819708857

ISBN: (纸本)9789819708840

Drug combination therapy holds great promise for curing cancer patients, as it can significantly enhance treatment effectiveness and reduce drug toxicity. However, efficiently identifying synergistic drug combinations from a vast pool of potential drug combinations remains challenging, mainly due to the expensive and time-consuming nature of traditional experimental methods. In this work, we introduce a novel deep learning method called SNAADC for discovering synergistic drug combinations. In SNAADC, we employ Siamese Network and attention mechanism to extract more effective drug features for better performance. The experimental results demonstrate that SNAADC outperforms traditional and popular methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Network architecture

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Fault detection for delay-switched systems with all subsystems unstable 41

Fault detection for delay-switched systems with all subsyste...

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第41届中国控制会议

作者： Qingyu Su Yufu Guo Jian Li School of Automation Engineering Northeast Electric Power University Jilin Provincial Key Laboratory of Advanced Control Technology of Smart Energy

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The fault detection problem of a class of linear discrete switched systems with time delay is studied,where the subsystems of the systems are all *** main idea of this article is to design a fault detection filter to turn the detection problem into a H filter *** this paper,we use a special dwell time and Lyapunov function,introduce the weighted fault matrix,and the sufficient conditions for the stability of the augmented systems are obtained by using the linear matrix inequality ***,an example is used to verify the effectiveness of the fault detection filter designed in this paper.

关键词： Fault detection Switched systems Time delay Unstable subsystems

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Learning Knowledge Evolution with Time Duration from Finer-Time-Granularity Temporal Knowledge Graph

Learning Knowledge Evolution with Time Duration from Finer-T...

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2023 China automation Congress, CAC 2023

作者： Du, Shaochong Chen, Kang Yang, Shijie Huo, Hong Fang, Tao Shanghai Jiao Tong University Department of Automation Shanghai China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350303759

How to represent the temporal information corresponding to each fact in temporal knowledge graphs (TKGs) effectively is always challenging. Most existing representation learning methods usually map the timelines of knowledges into multiple points and ignore the underlying continuous time property and periodic characteristics behind those dense timestamps in finer-time granularity temporal knowledge graphs. A novel Knowledge Evolution with Time Duration (KETD) model is proposed for knowledge representation of temporal knowledge graphs with finer-time granularities. It represents the entity embedding as a time-varying nonlinear function to find the specific continuous time property from dense timestamps. To the best of our knowledge, it is the first attempt to learn embeddings of time durations and combines them into embeddings of entities and relations to predict potential periodic facts. It also uses the temporal point process to capture the impact of historical facts on the current fact. The experiments on self-built finer-time granularity TKG of Satellite-to-Earth Communication (STEC) and two public datasets have demonstrated the superiority of KETD compared to some baseline approaches. © 2023 IEEE.

关键词： Knowledge graph

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Compensation of the Temperature Impact on the Characteristics of a Titania-Silica Thin Film Humidity Sensor Element

Compensation of the Temperature Impact on the Characteristic...

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2023 International Conference Automatics and Informatics, ICAI 2023

作者： Ivanov, Stefan Nedev, Nedyu Nenova, Zvezditza Technical University of Gabrovo Department of Automation Information and Control Systems Gabrovo Bulgaria Technical University of Gabrovo Department of Fundamentals of Electrical and Power Engineering Gabrovo Bulgaria

ISBN: (纸本)9798350312911

In the present work is investigated the impact of ambient temperature in the range of 20°C to 50°C under a change in relative humidity RH of 20% up to 92 % on the characteristics of a highly sensitive TiO2-SiO2-based thin-film impedance humidity sensor element doped with Ce and prepared by a sol-gel method. The variation of sensor impedance changes in a very wide range - about 4 orders of magnitude. The sensor element is connected in a measurement circuit based on an AC bridge, a variable gain amplifier, a precision rectifier, and a microcontroller with a built-in analog-to-digital converter. The use of artificial neural networks monitoring the ambient temperature and measured voltage is proposed for the realization of the temperature compensation of the characteristics. The proposed approach allows compensating the impact of temperature and performing measurements when connecting humidity sensing elements with a very wide range of impedance change. © 2023 IEEE.

关键词： Silica

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Optimizing Maximum Profit for Electric Vehicle Users in a Bipolar DC Distribution Grid with Probabilistic EV Load Demand and V2G Integration 12

Optimizing Maximum Profit for Electric Vehicle Users in a Bi...

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12th International Electrical engineering Congress, iEECON 2024

作者： Sakulphaisan, Guntinan Son-In, Sirirat Junhuathon, Nitikorn Pathumwan Institute Of Technology Industrial Technology And Innovation Management Faculty Of Science And Technology Bangkok Thailand Bansomdejchaopraya Rajabhat University Electrical Engineering And Automation Control Systems Faculty Of Engineering And Industrial Technology Bangkok Thailand Rajamangala University Of Technology Thanyaburi Faculty Of Engineering Department Of Electrical Engineering Pathumthani Thailand

ISBN: (纸本)9798350383591

This article delves into the synergistic potential of integrating Bipolar DC distribution grids, Probabilistic EV load demand forecasting, and Vehicle-to-Grid (V2G) technology. It offers a blueprint for electric vehicle (EV) users to smartly improve their financial results. Through the amalgamation of these components, individuals who possess electric vehicles have the potential to mitigate their energy expenditures while concurrently generating additional income. The study reveals that the integration of EV into the distribution system can lead to a substantial increase in daily energy loss, reaching up to 25.91%. However, when V2G technology is employed within the distribution grid, it has the remarkable capability to mitigate this increase in daily energy loss significantly, achieving a reduction of up to 64.12%. © 2024 IEEE.

关键词： Integration

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Hawk and pigeon's intelligence for UAV swarm dynamic combat game via competitive learning pigeon-inspired optimization

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Science China(Technological Sciences) 2022年第5期65卷 1072-1086页

作者： YU YuePing LIU JiChuan WEI Chen School of Automation Science and Electrical Engineering Beihang UniversityBeijing100083China School of Electronic Engineering Xidian UniversityXi’an710071China Hebei Key Laboratory of Electromagnetic Spectrum Cognition and Control The 54th Research Institute of CETCShijiazhuang050081China

For unmanned aerial vehicle(UAV)swarm dynamic combat,swarm antagonistic motion control and attack target allocation are extremely challenging *** this paper,the competitive learning pigeon-inspired optimization(CLPIO)algorithm is proposed to handle the cooperative dynamic combat problem,which integrates the distributed swarm antagonistic motion and centralized attack target ***,the threshold trigger strategy is presented to switch two *** seek a feasible and optimal combat scheme,a dynamic game approach combined with hawk grouping mechanism and situation assessment between sub-groups is designed to guide the solution of the optimal attack scheme,and the model of swarm antagonistic motion imitating pigeon’s intelligence is proposed to form a confrontation *** analysis of the CLPIO algorithm shows its convergence in theory and the comparison with the other four metaheuristic algorithms shows its superiority in solving the mixed Nash equilibrium ***,numerical simulation verifis that the proposed methods can provide an effective combat scheme in the set scenario.

关键词： unmanned aerial vehicle(UAV) competitive learning pigeon-inspired optimization(CLPIO) swarm antagonistic motion attack target allocation dynamic game theory

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Cascading Delays for the High-Speed Rail Network Under Different Emergencies:A Double Layer Network Approach

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IEEE/CAA Journal of Automatica Sinica 2023年第10期10卷 2014-2025页

作者： Xingtang Wu Mingkun Yang Wenbo Lian Min Zhou Hongwei Wang Hairong Dong School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Control and Computer Engineering North China Electric Power UniversityBeijing 100096China State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong UniversityBeijing 100044China National Research Center of Railway Safety Assessment Beijing Jiaotong UniversityBeijing 100044China

High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading delays on a network scale. Studying the delay propagation mechanism could help to improve the timetable resilience in the planning stage and realize cooperative rescheduling for dispatchers. To quickly and effectively predict the spatial-temporal range of cascading delays, this paper proposes a max-plus algebra based delay propagation model considering trains’ operation strategy and the systems’ constraints. A double-layer network based breadth-first search algorithm based on the constraint network and the timetable network is further proposed to solve the delay propagation process for different kinds of emergencies. The proposed model could deal with the delay propagation problem when emergencies occur in sections or stations and is suitable for static emergencies and dynamic emergencies. Case studies show that the proposed algorithm can significantly improve the computational efficiency of the large-scale HSR network. Moreover, the real operational data of China HSR is adopted to verify the proposed model, and the results show that the cascading delays can be timely and accurately inferred, and the delay propagation characteristics under three kinds of emergencies are unfolded.

关键词： Delay propagation double layer network high speed rail network max-plus algebra

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Spatial information considered convolutional neural network for electroencephalogram-based motor imagery classification 3

Spatial information considered convolutional neural network ...

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3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2023

作者： Shi, Hongbing Zhang, Jinhui Pei, Zhongcai School of Automation Science and Electrical Engineering Beihang University Beijing China North Information Control Research Institute Group Co. Ltd. China

ISBN: (数字)9781510667617

ISBN: (纸本)9781510667600

As brain-computer interface (BCI) technology continues to advance in various fields, it has become one of the possible solutions for patients with motor dysfunction who have healthy thinking ability to regain motor ability. The vigorous development of deep learning (DL) provides it with a possible tool to analyze electroencephalogram (EEG) signals. Through analyzing and categorizing EEG signals associated with motor imagery (MI), the system can effectively perceive the patient's motor intentions. Currently, Convolutional Neural Networks (CNN) have exhibited exceptional performance in a variety of fields, including computer vision (CV) and natural language processing (NLP). However, the brain structure has rich spatial information, which was not fully utilized by CNN for MI-EEG signal analysis in the past. This paper introduces SP-CNN, a convolutional neural network that incorporates spatial information from the brain, to address the classification challenge of MI-EEG signals. The experimental findings indicate that this method exhibits stable and robust performance across diverse subjects. © 2023 SPIE.

关键词： Electroencephalography

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Intermittent control for Fixed-Time Synchronization of Coupled Networks

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IEEE/CAA Journal of Automatica Sinica 2023年第6期10卷 1488-1490页

作者： Yongbao Wu Ziyuan Sun Guangtao Ran Lei Xue the School of Automation Southeast UniversityNanjing 210096China the Department of Applied Mathematics University of WaterlooOntario N2J 4N3Canada the Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China

Dear Editor, This letter deals with fixed-time synchronization(Fd-TS) of complex networks(CNs) under aperiodically intermittent control(AIC)for the first time. The average control rate and a new Lyapunov function are ... 详细信息

关键词： synchronization Synchronization overcome

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Analysis and State Feedback control Bifurcation of Fractional-Order Cyclic Gene Regulatory Networks with Time Delay 41

Analysis and State Feedback Control Bifurcation of Fractiona...

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第41届中国控制会议

作者： Feng Liu Shujiang Sun Juan Zhao Feiyue Zhuo Hua O Wang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,a fractional-order cyclic gene regulatory network model with time delay is ***,the total time delay of the system is selected as the bifurcation parameter,and the condition for the existence of Hopf bifurcation is derived by analyzing its characteristic *** is found that the time delay affects the stability of the system,and the order affects the position of the bifurcation *** the time delay is greater than the critical time delay,the system loses ***,a state feedback controller is designed for the unstable *** is proved that the control method has good control effect for the system instability caused by Hopf ***,the correctness of the theoretical derivation is verified by simulation.

关键词： Fractional-order cyclic gene regulatory network Hopf bifurcation feedback control time delay

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