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A single micro-LED manipulation system based on micro-gripper

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Nanotechnology and Precision engineering 2024年第2期7卷 45-52页

作者： Jie Bai Pingjuan Niu Erdan Gu Jianming Li Clarence Augustine TH Tee school of Mechanical engineering Tiangong University school of Electronic and information engineering Tiangong University Institute of Photonics University of Strathclyde Tianjin Key Laboratory of Micro Low Gravity Environment Simulation Technology Tianjin Aerospace Electromechanical Equipment Research Institute Department of Electrical and information engineering School of Physics and Electrical Information EngineeringZhejiang Normal University

Micro-LEDs(μLEDs) have advantages in terms of brightness, power consumption, and response speed. In addition, they can also be used as micro-sensors implanted in the body via flexible electronic skin. One of the key techniques involved in the fabrication of μLED-based devices is transfer printing. Although numerous methods have been proposed for transfer printing, improving the yield of μLED arrays is still a formidable task. In this paper, we propose a novel method for improving the yield of μLED arrays transferred by the stamping method, using an innovative design of piezoelectrically driven asymmetric micro-gripper. Traditional grippers are too large to manipulate μLEDs, and therefore two micro-sized cantilevers are added at the gripper tips. A μLED manipulation system is constructed based on the micro-gripper together with a three-dimensional positioning system. Experimental results using this system show that it can be used successfully to manipulate μLED arrays.

关键词： Micro-gripper Micro-LED Transfer printing Manipulation

Comprehensive Exergoeconomic Analysis and Optimization of a Novel Zero-Carbon-Emission Multi-Generation System based on Carbon Dioxide Cycle

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Journal of Thermal Science 2024年第3期33卷 1065-1081页

作者： SUN Yan LI Hongwei WANG Di DU Changhe school of Energy and Power engineering Northeast Electric Power UniversityJilin132012China school of Automation engineering Northeast Electric Power UniversityJilin132012China Xi’an Institute of electromechanical information Technology Xi’an710065China

This paper aims to conduct a comprehensive exergoeconomic analysis of a novel zero-carbon-emission multi-generation system and propose a fast optimization method combined with machine *** detailed exergoeconomic analysis of a novel combined power,freshwater and cooling multi-generation system is performed in this *** exergoeconomic analysis model is established by exergy flow theory.A comprehensive exergy,exergoeconomic and environmental analysis is carried *** critical decision variables are researched to bring out effects on the multi-generation system exergoeconomic performance.A novel fast optimization method combining genetic algorithm and Bagging neural network is *** advanced nature comparison is made between the proposed system and four similar *** display that increasing the turbine inlet temperature can improve exergy efficiency and decrease the total product unit *** multi-generation system exergy destruction directly determines exergy efficiency and total exergy destruction cost *** total product unit cost in the cost optimal design case is reduced by 7.7%and 25%,respectively,compared with exergy efficiency optimal design case and basic design *** with four similar cases,the proposed multi-generation system has great advantages in thermodynamic performance and exergoeconomic *** paper can provide research methods and ideas for performance analysis and fast optimization of multi-generation system.

关键词： waste heat recovery exergoeconomic analysis supercritical carbon dioxide optimization machine learning

Underdetermined direction of arrival estimation with nonuniform linear motion sampling based on a small unmanned aerial vehicle platform

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Defence Technology（防务技术） 2024年第3期33卷 352-363页

作者： Xinwei Wang Xiaopeng Yan Tai An Qile Chen Dingkun Huang Science and Technology on electromechanical Dynamic Control Laboratory School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China

Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical *** improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation *** the motion of the UAV platform,the echo signal is sampled at different ***,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal *** the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of *** results of numerical simulations conducted herein verify the superior performance of the proposed method.

关键词： Unmanned aerial vehicle(UAV) Uniform linear array(ULA) Direction of arrival(DOA) Difference co-array Nonuniform linear motion sampling method

Cognitive interference decision method for air defense missile fuze based on reinforcement learning

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Defence Technology（防务技术） 2024年第2期32卷 393-404页

作者： Dingkun Huang Xiaopeng Yan Jian Dai Xinwei Wang Yangtian Liu Science and Technology on electromechanical Dynamic Control Laboratory School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China

To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is ***,dividing the distance between the missile and the target into multiple states to increase the quantity of state ***,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference *** interference effect is determined by detecting whether the fuze signal ***,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference *** effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile *** optimal interference form for each distance state has been *** with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.

关键词： Cognitive radio Interference decision Radio fuze Reinforcement learning Interference strategy optimization

On the size generalizibility of graph neural networks for learning resource allocation

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Science China(information Sciences) 2024年第4期67卷 239-254页

作者： Jiajun WU Chengjian SUN Chenyang YANG Beihang University school of Electronics and information engineering

Size generalization is important for learning resource allocation policies in wireless systems with time-varying scales. If a neural network for learning a wireless policy is not generalizable to the size of its input, it has to be re-trained whenever the system scale changes, which hinders its practical use due to the unaffordable training costs. Graph neural networks(GNNs) have been shown with size generalization ability empirically when optimizing resource allocation. Yet, are GNNs naturally size generalizable? In this paper,we argue that GNNs are not always size generalizable for resource allocation. We find that the aggregation and activation functions of the GNNs for learning a class of wireless policies play a key role in their size generalization ability. We take the GNN with the mean aggregator, called mean-GNN, as an example to reveal a size generalization condition. To demonstrate how to satisfy the condition, we learn power and bandwidth allocation policies for ultra-reliable low-latency communications and show that selecting or pretraining the activation function in the output layer of mean-GNN can make the GNN size *** results validate our analysis and evaluate the performance of the learned policies.

关键词： size generalization graph neural networks resource allocation permutation equivariance

Protein acetylation sites with complex-valued polynomial model

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Frontiers of Computer Science 2024年第3期18卷 217-226页

作者： Wenzheng BAO Bin YANG school of information engineering Xuzhou University of TechnologyXuzhou 221018China school of information Science and engineering Zaozhuang UniversityZaozhuang 277160China

Protein acetylation refers to a process of adding acetyl groups(CH3CO-)to lysine residues on protein *** one of the most commonly used protein post-translational modifications,lysine acetylation plays an important role in different *** our study,we developed a humanspecific method which uses a cascade classifier of complexvalued polynomial model(CVPM),combined with sequence and structural feature descriptors to solve the problem of imbalance between positive and negative *** gene expression programming and differential evolution are utilized to search the optimal CVPM *** also made a systematic and comprehensive analysis of the acetylation data and the prediction *** performances of our proposed method are 79.15%in Sp,78.17%in Sn,78.66%in ACC 78.76%in F1,and 0.5733 in MCC,which performs better than other state-of-the-art methods.

关键词： protein acetylation complex-valued polynomial model machine learning

Visible Light Indoor Positioning System Based on Pisarenko Harmonic Decomposition and Neural Network

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Chinese Journal of Electronics 2024年第1期33卷 195-203页

作者： Li ZHAO Yi REN Qi WANG Lange DENG Feng ZHANG school of Electronic information engineering Xi’an Technological University

Visible-light indoor positioning is a new generation of positioning technology that can be integrated into smart lighting and optical communications. The current received signal strength(RSS)-based visible-light positioning systems struggle to overcome the interferences of background and indoor-reflected noise. Meanwhile, when ensuring the lighting, it is impossible to use the superposition of each light source to accurately distinguish light source information; furthermore, it is difficult to achieve accurate positioning in complex indoor environments. This study proposes an indoor positioning method based on a combination of power spectral density detection and a neural network. The system integrates the mechanism for visible-light radiation detection with RSS theory, to build a back propagation neural network model fitting for multiple reflection channels. Different frequency signals are loaded to different light sources at the beacon end, and the characteristic frequency and power vectors are obtained at the location end using the Pisarenko harmonic decomposition method. Then, a complete fingerprint database is established to train the neural network model and conduct location tests. Finally, the location effectiveness of the proposed algorithm is verified via actual positioning experiments. The simulation results show that, when four groups of sinusoidal waves with different frequencies are superimposed with white noise, the maximum frequency error is 0.104 Hz and the maximum power error is 0.0362 W. For the measured positioning stage, a 0.8 m × 0.8 m × 0.8 m solid wood stereoscopic positioning model is constructed, and the average error is 4.28 cm. This study provides an effective method for separating multi-source signal energies, overcoming background noise, and improving indoor visible-light positioning accuracies.

关键词： Neural networks Measurement uncertainty Position measurement Harmonic analysis Light emitting diodes Frequency estimation Indoor positioning systems

Data-driven active vibration control for helicopter with trailing-edge flaps using adaptive dynamic programming

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Chinese Journal of Aeronautics 2024年第6期37卷 151-166页

作者： Yu CHEN Qun ZONG Xiuyun ZHANG Jinna LI school of Electrical and information engineering Tianjin UniversityTianjin 300072China school of information and Control engineering Liaoning Petrochemical UniversityFushun 113001China

The helicopter Trailing-Edge Flaps(TEFs)technology is one of the recent hot topics in morphing wing *** employing controlled deflection,TEFs can effectively reduce the vibration level of ***,designing specific vibration reduction control methods for the helicopters equipped with trailing-edge flaps is of significant practical *** paper studies the optimal control problem for helicopter-vibration systems with TEFs under the framework of adaptive dynamic programming combined with Reinforcement Learning(RL).Time-delay and disturbances,caused by complexity of helicopter dynamics,inevitably deteriorate the control performance of vibration *** solve this problem,a zero-sum game formulation with a linear quadratic form for reducing vibration of helicopter systems is presented with a virtual *** this context,an off-policy reinforcement learning algorithm is developed to determine the optimal control *** algorithm utilizes only vertical vibration load data to achieve a policy that reduces vibration,attains Nash equilibrium,and addresses disturbances while compensating for time-delay without knowledge of the dynamics of the helicopter *** effectiveness of the proposed method is demonstrated in a virtual platform.

关键词： Active control Adaptive dynamic program-ming Helicopter rotor Vibration control Zero-sum game

Full-domain collaborative deployment method of multiple interference sources and evaluation of its deployment effect

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Defence Technology（防务技术） 2024年第2期32卷 572-595页

作者： Yue Wang Fuping Sun Xian Wang Jinming Hao Kai Xiao school of Geospatial information The PLA Information Engineering UniversityZhengzhou 450001HenanChina

This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the attacker and the capability to defend the GNSS during navigation *** evaluation indicators for the jamming effect of GNSS suppressive and deceptive jamming sources are first created,their evaluation models are built,and their detection procedures are sorted out,as the basis for determining the deployment *** principles for collaboratively deploying multi-jamming sources are developed to obtain the deployment structures(including the required number,structures in demand,and corresponding positions)of three single interference sources required by collaboratively ***,simulation and hardware-in-loop testing results are presented to determine a rational configuration of the collaborative deployment of multi-jamming sources in the set situation and further realize the full-domain deployment of an interference network from ground,air to *** evaluation indices for the deployment effect are finally developed to evaluate the deployment effect of the proposed configuration and further verify its reliability and rationality.

关键词： Jamming effect Multiple interference sources Collaborative deployment Effect evaluation Defense capability