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Review of Key Technologies for Developing Personalized Lower Limb Rehabilitative Exoskeleton Robots TAO Jing, (陶璟), ZHOU Zhenhuan (周振欢) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 16-28.   DOI: 10.1007/s12204-022-2452-3 Abstract （1494）      PDF（pc） （1179KB）（1975）       Knowledge map    Save Rehabilitative training and assistance to daily living activities play critical roles in improving the life quality of lower limb dyskinesia patients and older people with motor function degeneration. Lower limb rehabilitative exoskeleton has a promising application prospect in support of the above population. In this paper, critical technologies for developing lower limb rehabilitative exoskeleton for individualized user needs are identi- fied and reviewed, including exoskeleton hardware modularization, bionic compliant driving, individualized gait planning and individual-oriented motion intention recognition. Inspired by the idea of servitization, potentials in exoskeleton product-service system design and its enabling technologies are then discussed. It is suggested that future research will focus on exoskeleton technology and exoskeleton-based service development oriented to an individual’s physical features and personalized requirements to realize better human-exoskeleton coordination in terms of technology, as well as accessible and high-quality rehabilitation and living assistance in terms of utility. Reference | Related Articles | Metrics | Comments（0）

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Review on Anti-Frost Technology Based on Microchannel Heat Exchanger YE Zhenhong(叶振鸿), WANG Wei(王炜), LI Xinhua(李新华), CHEN Jiangping(陈江平) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 161-178.   DOI: 10.1007/s12204-022-2539-x Abstract （596）      PDF（pc） （4397KB）（805）       Knowledge map    Save Frosting is an inevitable adverse phenomenon in many fields such as industrial refrigeration, cryogenics, and heat pump air conditioning, which may influence the efficiency of the equipment and increase the energy consumption of the system. The complicated louvered-fin structure and fluid-channels arrangements of the microchannel heat exchanger (HEX) will affect the heat transfer performance and frosting characteristics. First, this article analyzes different factors such as refrigerant distribution, refrigerant flow pattern, and HEX surface temperature distribution. Further, combined with the features of the microchannel HEX, the existing anti-frosting technologies and various methods of surface treatment for anti-frosting are summarized. The review focuses on the preparation of superhydrophobic surfaces and their superior properties. Furthermore, the internal mechanism is analyzed in conjunction with the relevant research of our group. Superhydrophobic character has excellent anti-frosting performance and heat transfer performance, which is of great significance for improving energy-saving and system performance. Finally, the future development of superhydrophobic surface technology is analyzed and prospected. Reference | Related Articles | Metrics | Comments（0）

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A Novel Cable-Driven Soft Robot for Surgery LI Ru1 (李茹), CHEN Fang2 (陈方), YU Wenwei3 (俞文伟), IGARASH Tatsuo3,4, SHU Xiongpeng1 (舒雄鹏), XIE Le1,5,6∗ (谢叻) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 60-72.   DOI: 10.1007/s12204-022-2497-3 Abstract （511）      PDF（pc） （2939KB）（698）       Knowledge map    Save Robot-assisted laparoscopic radical prostatectomy (RARP) is widely used to treat prostate cancer. The rigid instruments primarily used in RARP cannot overcome the problem of blind areas in surgery and lead to more trauma such as more incision for the passage of the instrument and additional tissue damage caused by rigid instruments. Soft robots are relatively flexible and theoretically have infinite degrees of freedom which can overcome the problem of the rigid instrument. A soft robot system for single-port transvesical robot-assisted radical prostatectomy (STvRARP) is developed in this study. The soft manipulator with 10 mm in diameter and a maximum bending angle of 270? has good flexibility and dexterity. The design and mechanical structure of the soft robot are described. The kinematics of the soft manipulator is established and the inverse kinematics is compensated based on the characteristics of the designed soft manipulator. The master-slave control system of soft robot for surgery is built and the feasibility of the designed soft robot is verified. Reference | Related Articles | Metrics | Comments（0）

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Transfer Learning in Motor Imagery Brain Computer Interface: A Review LI Mingai1,2,3∗ (李明爱), XU Dongqin1 (许东芹) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 37-59.   DOI: 10.1007/s12204-022-2488-4 Abstract （511）      PDF（pc） （1734KB）（595）       Knowledge map    Save Transfer learning, as a new machine learning methodology, may solve problems in related but different domains by using existing knowledge, and it is often applied to transfer training data from another domain for model training in the case of insufficient training data. In recent years, an increasing number of researchers who engage in brain-computer interface (BCI), have focused on using transfer learning to make most of the available electroencephalogram data from different subjects, effectively reducing the cost of expensive data acquisition and labeling as well as greatly improving the learning performance of the model. This paper surveys the development of transfer learning and reviews the transfer learning approaches in BCI. In addition, according to the “what to transfer” question in transfer learning, this review is organized into three contexts: instance-based transfer learning, parameter-based transfer learning, and feature-based transfer learning. Furthermore, the current transfer learning applications in BCI research are summarized in terms of the transfer learning methods, datasets, evaluation performance, etc. At the end of the paper, the questions to be solved in future research are put forward, laying the foundation for the popularization and in-depth research of transfer learning in BCI. Reference | Related Articles | Metrics | Comments（0）

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Review of Power-Assisted Lower Limb Exoskeleton Robot HE Guisong (贺贵松), HUANG Xuegong (黄学功), LI Feng (李峰), WANG Huixing (汪辉兴) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 1-15.   DOI: 10.1007/s12204-022-2489-3 Abstract （1502）      PDF（pc） （1195KB）（584）       Knowledge map    Save Power-assisted lower limb exoskeleton robot is a wearable intelligent robot system involving mechanics,materials, electronics, control, robotics, and many other fields. The system can use external energy to provide additional power to humans, enhance the function of the human body, and help the wearer to bear weight that is previously unbearable. At the same time, employing reasonable structure design and passive energy storage can also assist in specific actions. First, this paper introduces the research status of power-assisted lower limb exoskeleton robots at home and abroad, and analyzes several typical prototypes in detail. Then, the key technologies such as structure design, driving mode, sensing technology, control method, energy management, and human-machine coupling are summarized, and some common design methods of the exoskeleton robot are summarized and compared. Finally, the existing problems and possible solutions in the research of power-assisted lower limb exoskeleton robots are summarized, and the prospect of future development trend has been analyzed. Reference | Related Articles | Metrics | Comments（0）

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How Will Dynamic Charging Tariff Affect Electric Truck Fleet Operation: A Two-Stage Stochastic Model DENG Jiali (邓佳莉), HU Hao∗ (胡昊), DAI Lei (戴磊) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1050-1062.   DOI: 10.1007/s12204-022-2556-9 Abstract （230）      PDF（pc） （914KB）（570）       Knowledge map    Save Technical advances and sustainable development tendency accelerate the implementation of electric trucks. However, the penetration of dynamic charging tariff policy poses a huge challenge to the cost-optimal operation of the electric truck fleet. To this end, a two-stage stochastic electric vehicle routing model is formulated to support cost-efficient routing and charging decisions. Furthermore, an experimental study based on a real-world distribution network is conducted to evaluate impacts of dynamic charging tariffs on logistics planning. The results show that the daily operation cost can reduce by 3.57% to 5.55% as the number of dynamic charging stations increases. The value of stochastic solution confirms the benefits of implementing stochastic programming model,which will ensure a lower operation cost in the long-term through robust route planning. Reference | Related Articles | Metrics | Comments（0）

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Multi-Agent Path Planning Method Based on Improved Deep Q-Network in Dynamic Environments LI Shuyi (李舒逸), LI Minzhe (李旻哲), JING Zhongliang∗ (敬忠良) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 601-612.   DOI: 10.1007/s12204-024-2732-1 Abstract （1238）      PDF（pc） （1213KB）（533）       Knowledge map    Save The multi-agent path planning problem presents significant challenges in dynamic environments, primarily due to the ever-changing positions of obstacles and the complex interactions between agents’ actions. These factors contribute to a tendency for the solution to converge slowly, and in some cases, diverge altogether. In addressing this issue, this paper introduces a novel approach utilizing a double dueling deep Q-network (D3QN), tailored for dynamic multi-agent environments. A novel reward function based on multi-agent positional constraints is designed, and a training strategy based on incremental learning is performed to achieve collaborative path planning of multiple agents. Moreover, the greedy and Boltzmann probability selection policy is introduced for action selection and avoiding convergence to local extremum. To match radar and image sensors, a convolutional neural network - long short-term memory (CNN-LSTM) architecture is constructed to extract the feature of multi-source measurement as the input of the D3QN. The algorithm’s efficacy and reliability are validated in a simulated environment, utilizing robot operating system and Gazebo. The simulation results show that the proposed algorithm provides a real-time solution for path planning tasks in dynamic scenarios. In terms of the average success rate and accuracy, the proposed method is superior to other deep learning algorithms, and the convergence speed is also improved. Reference | Related Articles | Metrics | Comments（0）

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Medical Image Encryption Based on Josephus Traversing and Hyperchaotic Lorenz System YANG Na (杨娜), ZHANG Shuxia (张淑霞), BAI Mudan (白牡丹), LI Shanshan∗ (李珊珊) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 91-108.   DOI: 10.1007/s12204-022-2555-x Abstract （383）      PDF（pc） （8082KB）（419）       Knowledge map    Save This study proposes a new medical image encryption scheme based on Josephus traversing and hyperchaotic Lorenz system. First, a chaotic sequence is generated through hyperchaotic system. This hyperchaotic sequence is used in the scrambling and diffusion stages of the algorithm. Second, in the scrambling process, the image is initially confused by Josephus scrambling, and then the image is further confused by Arnold map. Finally, generated hyperchaos sequence and exclusive OR operation is used for the image to carry on the positive and reverse diffusion to change the pixel value of the image and further hide the effective information of the image. In addition, the information of the plaintext image is used to generate keys used in the algorithm, which increases the ability of resisting plaintext attack. Experimental results and security analysis show that the scheme can effectively hide plaintext image information according to the characteristics of medical images, and is resistant to common types of attacks. In addition, this scheme performs well in the experiments of robustness, which shows that the scheme can solve the problem of image damage in telemedicine. It has a positive significance for the future research. Reference | Related Articles | Metrics | Comments（0）

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Multi-Robot Task Allocation Using Multimodal Multi-Objective Evolutionary Algorithm Based on Deep Reinforcement Learning MIAO Zhenhua(苗镇华), HUANG Wentao(黄文焘), ZHANG Yilian(张依恋), FAN Qinqin(范勤勤) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 377-387.   DOI: 10.1007/s12204-023-2679-7 Abstract （1178）      PDF（pc） （975KB）（392）       Knowledge map    Save The overall performance of multi-robot collaborative systems is significantly affected by the multirobot task allocation. To improve the effectiveness, robustness, and safety of multi-robot collaborative systems,a multimodal multi-objective evolutionary algorithm based on deep reinforcement learning is proposed in this paper. The improved multimodal multi-objective evolutionary algorithm is used to solve multi-robot task allocation problems. Moreover, a deep reinforcement learning strategy is used in the last generation to provide a high-quality path for each assigned robot via an end-to-end manner. Comparisons with three popular multimodal multi-objective evolutionary algorithms on three different scenarios of multi-robot task allocation problems are carried out to verify the performance of the proposed algorithm. The experimental test results show that the proposed algorithm can generate sufficient equivalent schemes to improve the availability and robustness of multirobot collaborative systems in uncertain environments, and also produce the best scheme to improve the overall task execution efficiency of multi-robot collaborative systems. Reference | Related Articles | Metrics | Comments（0）

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Toughening Mechanism of Large Heat Input Weld Metal for Marine Engineering Extra-Thick Plate LENG Junjie1 (冷俊杰), DI Xinjie,2*1 (邸新杰), LI Chengning1,2 (利成宁), CHENG Shanghua3 (程尚华) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 349-360.   DOI: 10.1007/s12204-023-2638-3 Abstract （397）      PDF（pc） （4684KB）（315）       Knowledge map    Save In order to study the latest designed large heat input welding material of marine engineering extrathick plate, EH36 steel was joined by using twin-wire submerged arc welding with heat inputs of 85, 100 and 115 kJ/cm separately. Meanwhile, the microstructure and mechanical properties were evaluated to explore the toughening mechanism of weld metal. Results show that a lot of active inclusions are obtained in the weld metal due to the design idea of low carbon and oxide metallurgy, which contributes to the generation of numerous fine and interlocking acicular ferrite. The acicular ferrite volume ratio of weld metal exceeds 60%. Moreover, the impact energy at −40 ◦C surpasses 115 J and the crack tip opening displacement value at −10 ◦C is more than 0.2 mm under three heat inputs owing to the role of acicular ferrite, of which 85 kJ/cm is the best. The martensiteaustenite constituents are minor in size and the microstructure of the weld metal in reheated zone is dominated by small massive equiaxed ferrite, without impairing the toughness. As the heat input increases, the content of acicular ferrite drops and then rises; the impact toughness and fracture toughness first worsen consequently and then stabilize on account of the dramatic expansion of the proeutectoid ferrite size. Reference | Related Articles | Metrics | Comments（0）

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TshFNA-Examiner: A Nuclei Segmentation and Cancer Assessment Framework for Thyroid Cytology Image KE Jing1(柯晶), ZHU Junchao2 (朱俊超), YANG Xin1(杨鑫), ZHANG Haolin3 (张浩林), SUN Yuxiang1(孙宇翔), WANG Jiayi1(王嘉怡), LU Yizhou4(鲁亦舟), SHEN Yiqing5(沈逸卿), LIU Sheng6(刘晟), JIANG Fusong7(蒋伏松), HUANG Qin8(黄琴) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 945-957.   DOI: 10.1007/s12204-024-2743-y Abstract （455）      PDF（pc） （2836KB）（303）       Knowledge map    Save Examining thyroid fine-needle aspiration (FNA) can grade cancer risks, derive prognostic information, and guide follow-up care or surgery. The digitization of biopsy and deep learning techniques has recently enabled computational pathology. However, there is still lack of systematic diagnostic system for the complicated gigapixel cytopathology images, which can match physician-level basic perception. In this study, we design a deep learning framework, thyroid segmentation and hierarchy fine-needle aspiration (TshFNA)-Examiner to quantitatively profile the cancer risk of a thyroid FNA image. In the TshFNA-Examiner, cellular-intensive areas strongly correlated with diagnostic medical information are detected by a nuclei segmentation neural network; cell-level image patches are catalogued following The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) system, by a classification neural network which is further enhanced by leveraging unlabeled data. A cohort of 333 thyroid FNA cases collected from 2019 to 2022 from I to VI is studied, with pixel-wise and image-wise image patches annotated. Empirically, TshFNA-Examiner is evaluated with comprehensive metrics and multiple tasks to demonstrate its superiority to state-of-the-art deep learning approaches. The average performance of cellular area segmentation achieves a Dice of 0.931 and Jaccard index of 0.871. The cancer risk classifier achieves a macro-F1-score of 0.959, macro-AUC of 0.998, and accuracy of 0.959 following TBSRTC. The corresponding metrics can be enhanced to a macro-F1-score of 0.970, macro-AUC of 0.999, and accuracy of 0.970 by leveraging informative unlabeled data. In clinical practice, TshFNA-Examiner can help cytologists to visualize the output of deep learning networks in a convenient way to facilitate making the final decision. Reference | Related Articles | Metrics | Comments（0）

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Analysis of Software Trustworthiness Based on FAHP-CRITIC Method GAO Xiaotong11 (高晓彤), MA Yanfang1，2* (马艳芳), ZHOU Wei1 周伟) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 588-600.   DOI: 10.1007/s12204-022-2496-4 Abstract （279）      PDF（pc） （740KB）（301）       Knowledge map    Save Software trustworthiness includes many attributes. Reasonable weight allocation of trustworthy attributes plays a key role in the software trustworthiness measurement. In practical application, attribute weight usually comes from experts’ evaluation to attributes and hidden information derived from attributes. Therefore, when the weight of attributes is researched, it is necessary to consider weight from subjective and objective aspects. First, a novel weight allocation method is proposed by combining the fuzzy analytical hierarchy process (FAHP) method and the criteria importance though intercrieria correlation (CRITIC) method. Second, based on the weight allocation method, the trustworthiness measurement models of component-based software are established according to the seven combination structures of components. Third, the model reasonability is verified via proving some metric criteria. Finally, a case is carried out. According to the comparison with other models, the result shows that the model has the advantage of utilizing hidden information fully and analyzing the combination of components effectively. It is an important guide for measuring the trustworthiness measurement of component-based software. Reference | Related Articles | Metrics | Comments（0）

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Distributed Cooperative Anti-Disturbance Control for High-Order MIMO Nonlinear Multi-Agent Systems JIN Feiyu (金飞宇), CHEN Longsheng∗ (陈龙胜), LI Tongshuai (李统帅), SHI Tongxin (石童昕) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 656-666.   DOI: 10.1007/s12204-023-2673-0 Abstract （256）      PDF（pc） （680KB）（290）       Knowledge map    Save To solve the synchronization and tracking problems, a cooperative control scheme is proposed for a class of higher-order multi-input and multi-output (MIMO) nonlinear multi-agent systems (MASs) subjected to uncertainties and external disturbances. First, coupled relationships among Laplace matrix, leader-following adjacency matrix and consensus error are analyzed based on undirected graph. Furthermore, nonlinear disturbance observers (NDOs) are designed to estimate compounded disturbances in MASs, and a distributed cooperative antidisturbance control protocol is proposed for high-order MIMO nonlinear MASs based on the outputs of NDOs and dynamic surface control approach. Finally, the feasibility and effectiveness of the proposed scheme are proven based on Lyapunov stability theory and simulation experiments. Reference | Related Articles | Metrics | Comments（0）

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Reward Function Design Method for Long Episode Pursuit Tasks Under Polar Coordinate in Multi-Agent Reinforcement Learning DONG Yubo1 (董玉博), CUI Tao1 (崔涛), ZHOU Yufan1 (周禹帆), SONG Xun2 (宋勋), ZHU Yue2 (祝月), DONG Peng1∗ (董鹏) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 646-655.   DOI: 10.1007/s12204-024-2713-4 Abstract （460）      PDF（pc） （567KB）（277）       Knowledge map    Save Multi-agent reinforcement learning has recently been applied to solve pursuit problems. However, it suffers from a large number of time steps per training episode, thus always struggling to converge effectively, resulting in low rewards and an inability for agents to learn strategies. This paper proposes a deep reinforcement learning (DRL) training method that employs an ensemble segmented multi-reward function design approach to address the convergence problem mentioned before. The ensemble reward function combines the advantages of two reward functions, which enhances the training effect of agents in long episode. Then, we eliminate the non-monotonic behavior in reward function introduced by the trigonometric functions in the traditional 2D polar coordinates observation representation. Experimental results demonstrate that this method outperforms the traditional single reward function mechanism in the pursuit scenario by enhancing agents’ policy scores of the task. These ideas offer a solution to the convergence challenges faced by DRL models in long episode pursuit problems, leading to an improved model training performance. Reference | Related Articles | Metrics | Comments（0）

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Numerical Simulation of Radial Ultrasonic Assisted MIG Welding Arc HONG Lei1 (洪蕾), XIAO Hao1 (肖皓), YE Jia2 (叶佳), MA Guohong1* (马国红) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 330-338.   DOI: 10.1007/s12204-021-2380-7 Abstract （389）      PDF（pc） （1906KB）（274）       Knowledge map    Save The numerical simulation of arc was carried out for both conventional melt inert gas (MIG) welding and ultrasonic assisted melt inert gas (U-MIG) welding. Based on the model established by Fluent, the arc shape, temperature field, and potential distribution were simulated. The study found that the shape of the arc changed when ultrasonic was added radially; the high-temperature area of the arc stretched, and the temperature peak increased. But as the current increased, the increase in temperature decreased. In addition, under the same conditions, the potential of U-MIG decreased and the pressure on the workpiece increased. To verify the accuracy of the simulation results, welding experiments under identical conditions were carried out, and a high-speed camera was used to collect dynamic pictures of the arc. The simulation results were in a favorable agreement with the experimental results, which provided a certain reference value for ultrasonic assisted arc welding. Reference | Related Articles | Metrics | Comments（0）

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Arc and Droplet Behaviors in Horizontal Short-Arc Pulsed Gas Metal Arc Welding of 9%Ni Steel with ERNiCrMo-3 Welding Wire LIU Yiwei1 (刘轶玮), HUA Xueming1* (华学明), WU Dongsheng1 (吴东升), LI Fang1 (李芳), CAI Yan1 (蔡艳), WANG Huan2 (王欢), YANG Xiurong3 (杨修荣) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 361-376.   DOI: 10.1007/s12204-022-2548-9 Abstract （329）      PDF（pc） （5299KB）（262）       Knowledge map    Save Short-arc pulsed gas metal arc welding (P-GMAW) was used to solve the difficulties of molten pool spreading and droplet transfer of Ni-based welding wire. Suppression of short-circuit current was used to reduce spatter. Arc length stabilizer was used to acquire a proper and stable arc length maintained at the critical position where short circuit starts to occur. Short-arc P-GMAW with or without arc length stabilizer was compared. The droplet transfer, arc behaviors and weld bead profiles were investigated and compared based on the high-speed photography and observation of weld cross-section. When the arc length stabilizer was deactivated, the arc length was unstable and too short. The droplet transfer mode was mainly short circuit partial transfer, with only a small part of the droplet transferred into the molten pool, with the characteristics of no obvious necking, a few spatters, small droplet impact, long short circuit duration and high short-circuit current. There was also a small proportion of short circuit complete transfer with obvious necking, larger droplet impact, shorter short-circuit duration and lower short-circuit current. With arc length stabilizer, droplet transfer modes were short circuit complete transfer and spray transfer. The spray transfer had the largest droplet impact, no short circuit and no spatter. With the arc length stabilizer activated, a deep penetration, a high penetration ratio, a small reinforcement and a large reinforcement factor were acquired. This provides an innovative method to solve the difficulties of droplet transfer and molten pool spreading and eliminate the incomplete fusion in the GMAW of 9%Ni steel with nickel-based alloy welding wire. Reference | Related Articles | Metrics | Comments（0）

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Simulation of Pedestrian Evacuation Behavior Considering Dynamic Information Guidance in a Hub ZHOU Xuemei1, 2∗ (周雪梅), WEI Guohui1 (韦国辉), GUAN Zhen1 (关震), XI Jiaojiao1 (席姣姣) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1091-1102.   DOI: 10.1007/s12204-022-2560-0 Abstract （196）      PDF（pc） （1691KB）（260）       Knowledge map    Save : Simulation of pedestrians’ behavior in the hub can help decision-makers to formulate better evacuation strategies. With this aim, this study develops an improved cellular automata model considering pedestrian’s mass-following psychology and competitive awareness, and based on this model, pedestrian’s evacuation process from the channel of the hub with two exits is simulated. Moreover, dynamic guidance information, e.g., the realtime congestion situation of the evacuation routes, plays an important role during pedestrian evacuation processes in a hub, as the evaluation routes can be adjusted based on this information. That is, the congestion situation during the evaluation can be improved. Thus, dynamic signs are incorporated into the proposed model to study the influence of dynamic guidance information on pedestrian evacuation behavior. In simulation experiments, the influence of two parameters, namely the proportion of pedestrians unfamiliar with the hub and update interval of dynamic signs, on pedestrian evacuation behavior is studied. Results show that dynamic guidance information can improve the efficiency of pedestrian evacuation. In particular, the higher the proportion of pedestrians unfamiliar with the hub is, the more obvious the effect of dynamic guidance information is. Besides, different proportions of pedestrians unfamiliar with the hub lead to different update intervals of dynamic signs. Finally, the results of this study can provide some implications to the practical hub operation and evacuation, e.g., to standardize the order of evacuation routes and improve the information service level in the hub. Reference | Related Articles | Metrics | Comments（0）

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Wind Speed Short-Term Prediction Based on Empirical Wavelet Transform, Recurrent Neural Network and Error Correction ZHU Changsheng(朱昶胜), ZHU Lina∗ (朱丽娜) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 297-308.   DOI: 10.1007/s12204-022-2477-7 Abstract （461）      PDF（pc） （1282KB）（243）       Knowledge map    Save Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy. However, owing to the stochastic and intermittent of wind speed, predicting wind speed accurately is difficult. A new hybrid deep learning model based on empirical wavelet transform, recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper. The empirical wavelet transformation is applied to decompose the original wind speed series. The long short term memory network and the Elman neural network are adopted to predict low-frequency and highfrequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy. The error correction strategy based on deep long short term memory network is developed to modify the prediction errors. Four actual wind speed series are utilized to verify the effectiveness of the proposed model. The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction. Reference | Related Articles | Metrics | Comments（0）

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AlgoTime-Varying Formation-Containment Tracking Control for Unmanned Aerial Vehicle Swarm Systems with Switching Topologies and a Non-Cooperative Target WU Xiaojing∗(武晓晶), CAO Tongyao (曹童瑶), ZHEN Ran (甄然), LI Zhijie (李志杰) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 689-701.   DOI: 10.1007/s12204-024-2728-x Abstract （416）      PDF（pc） （1627KB）（240）       Knowledge map    Save This paper studies the time-varying formation-containment tracking control problems for unmanned aerial vehicle (UAV) swarm systems with switching topologies and a non-cooperative target, where the UAV swarm systems consist of one tracking-leader, several formation-leaders, and followers. The formation-leaders are required to accomplish a predefined time-varying formation and track the desired trajectory of the tracking-leader, and the states of the followers should converge to the convex hull spanned by those of the formation-leaders. First, a formation-containment tracking protocol is proposed with the neighboring relative information, and the feasibilit condition for formation-containment tracking and the algebraic Riccati equation are given. Then, the stability of the control system with the designed control protocol is proved by constructing a reasonable Lyapunov function. Finally, the simulation examples are applied to verify the effectiveness of the theoretical results. The simulation results show that both the formation tracking error and the containment error are convergent, so the system can complete the formation containment tracking control well. In the actual battlefield, combat UAVs need to chase and attack hostile UAVs, but sometimes when multiple UAVs work together for military interception, formationcontainment tracking control will occur. Reference | Related Articles | Metrics | Comments（0）

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Unidirectionally Sensitive Flexible Resistance Strain Sensor Based on AgNWs/PDMS LIU Xinyue, SUN Weiming, HE Mengfan, FANG Yuan, DJOULDE Aristide, DING Wei, LIU Mei, MENG Lingjun, WANG Zhiming J Shanghai Jiaotong Univ Sci    2025, 30 (2): 209-219.   DOI: 10.1007/s12204-024-2711-6 Abstract （369）      PDF（pc） （1725KB）（231）       Knowledge map    Save The flexible strain sensor has found widespread application due to its excellent flexibility, extensibility,  and adaptability to various scenarios.  This type of sensors face challenges in direction identification owing to  strong coupling between the principal strain and transverse resistance.  In this study, a silver nanowires (AgNWs)/polydimethylsiloxane (PDMS) strain sensor was developed, using a filtration method for preparing the AgNWs film which was then combined with PDMS to create a unidirectional, highly sensitive, fast-responsive,  and linear flexible strain sensor.  When the grid width is 0.25 mm, the AgNWs/PDMS strain sensor demonstrates  an outstanding unidirectional sensitivity, with a strain response solely along the parallel direction of the grid  lines (noise ratio α ≈ 8%), and a fast reaction time of roughly 106.99 ms.  In the end, this sensor’s ability to  detect curvature was also demonstrated through LEDs, demonstrating its potential applications in various fields,  including automotive, medical, and wearable devices. Reference | Related Articles | Metrics | Comments（0）

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Psychological Impact of the 2022 Round COVID-19 Pandemic on China’s College Students HONG Dongyang1,3 (洪冬羊), WANG Jinxia2,3 (王金霞), ZHANG Hongyang2,3 (张虹洋), CAO Ziyang2,3 (曹紫阳), YAN Zijun 2,3 (晏紫君), ZOU Lin2,3∗ (邹琳) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 141-149.   DOI: 10.1007/s12204-022-2557-8 Abstract （531）      PDF（pc） （194KB）（230）       Knowledge map    Save In response to the new round of COVID-19 outbreaks since March 2022, universities with high outbreak rates around the country have taken quarantine measures to contain the epidemic. Evidence from previous coronavirus outbreaks has shown that people under quarantine are at risk for mental health disorders. To better understand the impacts of this round of COVID-19 quarantine on domestic college students and their responses, we conducted a systematic survey to assess the stress and anxiety, and to evaluate effective measurements in this population. We searched relevant documents and literature, and designed a questionnaire from six aspects, including psychological status, epidemic situation, study, daily life, sports, and interpersonal communication, with 51 items in total. We sent the questionnaire on the Wenjuanxing Web platform, from April 2 to 8, 2022. We evaluated the mental status according to parts of the Generalized Anxiety Disorder-7 (GAD-7) and Depression Anxiety Stress Scales-21 (DASS-21), and investigated the influencing risk factors and countermeasures. Statistical analysis was performed by using the Chi-square test and multi-variable logistic regression. In total, 508 college respondents were recruited in our survey, and the pooled prevalence of mild anxiety (GAD score  5, or DASS-21 anxiety score 8) or stress (DASS-21 pressure score 14) caused by the new round of COVID-19 pandemic quarantine was 19.69% (100/508). The prevalence of the anxiety or stress in college students with COVID-19 quarantine between different genders, regions, and majors was not significantly different. Independent risk factors for the mild anxiety or stress of undergraduates by COVID-19 quarantine included learning efficiency or duration [OR = 1.36, 95%CI (1.14—1.62), P = 0.001], based on the combined analysis of Chi-square test analysis with multi-variable logistic regression analysis. Interestingly, the mental well-beings before COVID-19 epidemic quarantine [OR = 0.22, 95%CI (0.13—0.36), P < 0.000 1], more low-intensity exercise [OR = 0.36, 95%CI (0.15—0.87), P = 0.02, high-intensity exercise as reference], and good sleep quality [OR = 0.14, 95%CI (0.07—0.30), P < 0.000 1: OR = 0.42, 95%CI (0.30—0.59), P < 0.000 1] are protective factors for alleviating the quarantinecaused anxiety or stress in Chinese college students for this round of COVID-19 epidemic quarantine. During the round of COVID-19 epidemic quarantine in 2022, a small number of college students have mild anxiety, affected by decreased learning efficiency or duration, which could be mitigated with low-intensity exercise and good sleep quality. Reference | Related Articles | Metrics | Comments（0）

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Short-Term Effects of Ambient Air Pollutants on Outpatient Visits for Childhood Allergic Diseases in Shanghai, China HU Yi1 (户宜), GU Jianlei1 (顾坚磊), WU Dan1 (吴丹), WANG Xiaolei2 (王晓雷), LU Hui ¨ 1, 2 (吕晖), YU Guangjun1, 3∗ (于广军) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 979-994.   DOI: 10.1007/s12204-022-2454-1 Abstract （169）      PDF（pc） （1537KB）（227）       Knowledge map    Save This study aims to investigate the short-term effects of ambient air pollutants on outpatient visits for childhood allergic diseases. Daily data on ambient air pollutants (NO2, SO2, CO and PM2.5) and outpatient visits for childhood allergic diseases (asthma, atopic dermatitis and allergic rhinitis) were obtained in Shanghai, China from 2013 to 2014. The effects of ambient air pollutants were estimated for total outpatient visits for childhood allergic diseases, gender and age stratification and disease classification by using distributed lag non-linear model (DLNM). We found positive associations between short-term exposure to air pollutants and childhood allergic diseases. Girls and children aged  7 years old were more likely to be sensitive to ambient air pollutants. NO2 and SO2 showed stronger effects on asthma and atopic dermatitis, respectively. This study provides evidence that short-term exposure to ambient air pollutants can increase the risk of childhood allergic diseases. Reference | Related Articles | Metrics | Comments（0）

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Numerical Study of Wave Energy Converter Platform Geometry Layout Design PEI Feia (裴斐), LIN Yanb∗ (林焰) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 780-790.   DOI: 10.1007/s12204-022-2483-9 Abstract （216）      PDF（pc） （2088KB）（216）       Knowledge map    Save The present work is aimed at determining the optimal geometry layout of a wave energy converter platform for plate energy harvesting performance. A linear potential fluid theory method was applied to analyzing the interaction between the platform and plate. Three factors of layout geometry were tested and the performance of the plate was analyzed. The methodology of design of experiments was used to confirm factor significance and build response surface model. The 1st order model and the 2nd order model were built to describe the relation between factors and plate performance. The significance of two factors and their interactions were revealed, and an optimal parameter set was found. The wave form in front of the plate confirmed the interactions. It is clear that a wide entrance and enclosing channel for waves can maximize the plate performance. Reference | Related Articles | Metrics | Comments（0）

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Comfort Kneeling Seat for School-Age Children TANG Zhi1 (唐智), BAO Wenlan1 (鲍文岚), CHEN Xiaoyan1 (陈晓燕), ZHANG Weiran1 (章蔚然), LIU Jiaqin1 (刘佳沁), WANG Qian2∗ (王倩), JIANG Xinyu1 (姜鑫玉) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1009-1016.   DOI: 10.1007/s12204-022-2463-0 Abstract （232）      PDF（pc） （1270KB）（203）       Knowledge map    Save Kneeling seat is an ergonomic chair that can help the human body’s spine in a sitting posture to be closer to the natural state. In this study, we used non-contact camera method to measure visual distance. Using surface electromyography (sEMG) combined with subjective evaluation, we studied the obvious effects of seat angle and leg support angle in kneeling sitting posture on the ride comfort of healthy female school-age children without myopia. Using three experiment seat angles (10◦, 20◦ and 30◦), we found that as the sitting angle increased, the absolute value of the slope of the erector spinae linearity curve, MPF-t, gradually decreased. At 30◦, the slope of MPF-t was −0.26, the descent speed was the slowest, the activity of erector spinae was relatively lowest, and the comfort of children’s waist was also improved, while the comfort of calf gastrocnemius decreased, just the opposite. At the same time, leg support angles of 20◦, 30◦ and 40◦ were used. And in the study we found that the elevation of the leg support angle had no significant effect on the erector spinae muscle, but had a significant effect on the gastrocnemius muscle. When the leg support angle was 30◦, the slope of MPF-t was −0.42, and the gastrocnemius comfort reached its peak. Reference | Related Articles | Metrics | Comments（0）

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CBF-Based Distributed Model Predictive Control for Safe Formation of Autonomous Mobile Robots MU Jianbin∗ (穆建彬), YANG Haili (杨海丽), HE Defeng (何德峰) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 678-688.   DOI: 10.1007/s12204-024-2747-7 Abstract （402）      PDF（pc） （969KB）（195）       Knowledge map    Save A distributed model predictive control (DMPC) method based on robust control barrier function (RCBF) is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment. The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivitymaintenance. RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements, and security constraints are achieved through a combination. Then, the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation. To ensure safe control, the optimization problem is integrated with the DMPC method. Finally, the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives. Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security. Reference | Related Articles | Metrics | Comments（0）

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Motor Imagery Classification Based on Plain Convolutional Neural Network and Linear Interpolation LI Mingai1, 2∗ (李明爱), WEI Lina1 (魏丽娜) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 958-966.   DOI: 10.1007/s12204-022-2486-6 Abstract （277）      PDF（pc） （859KB）（185）       Knowledge map    Save Deep learning has been applied for motor imagery electroencephalogram (MI-EEG) classification in brain-computer system to help people who suffer from serious neuromotor disorders. The inefficiency network and data shortage are the primary issues that the researchers face and need to solve. A novel MI-EEG classification method is proposed in this paper. A plain convolutional neural network (pCNN), which contains two convolution layers, is designed to extract the temporal-spatial information of MI-EEG, and a linear interpolation-based data augmentation (LIDA) method is introduced, by which any two unrepeated trials are randomly selected to generate a new data. Based on two publicly available brain-computer interface competition datasets, the experiments are conducted to confirm the structure of pCNN and optimize the parameters of pCNN and LIDA as well. The average classification accuracy values achieve 90.27% and 98.23%, and the average Kappa values are 0.805 and 0.965 respectively. The experiment results show the advantage of the proposed classification method in both accuracy and statistical consistency, compared with the existing methods. Reference | Related Articles | Metrics | Comments（0）

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Comparative Study on Tissue Differentiation of Bone Marrow Mesenchymal Stem Cells in Irregular Versus Regular Bone Tissue Engineering Scaffolds Hai Jizhe, Xu Qingyu, Shan Chunlong, Li Haijie, Jing Lei J Shanghai Jiaotong Univ Sci    2025, 30 (4): 625-636.   DOI: 10.1007/s12204-025-2819-3 Abstract （145）      PDF（pc） （3038KB）（185）       Knowledge map    Save In bone tissue engineering microstructure design, adjusting the structural design of biomimetic bone scaffolds can provide distinct differentiation stimuli to cells on the scaffold surface. This study explored the biomechanical impacts of different biomimetic microstructures on advanced bone tissue engineering scaffolds. Two irregular bone scaffolds (homogeneous/radial gradient) based on the Voronoi tesselation algorithm and eight regular lattice scaffolds involving pillar body centered cubic, vintiles, diamond, and cube (homogeneous/radial gradient) with constant 80% porosity were constructed. Mechanical stimulation differentiation algorithms, finite element analysis, and computational fluid dynamics were used to investigate the effects of different pore structures on the octahedral shear strain and fluid flow shear stress within the scaffolds, thereby elucidating the differentiation capabilities of the five structural bone/cartilage cell types. The findings demonstrated that irregular structures and radial-gradient designs promoted osteogenic differentiation, whereas regular structures and homogeneous designs facilitated chondrogenic differentiation. The highest percentages of osteoblast and chondrocyte differentiation were observed in radial-gradient irregular scaffolds. This research provides insights into the microstructure design of bone tissue engineering implants. Reference | Related Articles | Metrics | Comments（0）

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Explosion Hazard Analysis of Liquefied Petroleum Gas Transportation GAO Sida1 (高思达),HAO Lin 1* (郝琳), ZHU Zhenxing2* (朱振兴), WEI Hongyuan1 (卫宏远) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 252-260.   DOI: 10.1007/s12204-022-2536-0 Abstract （416）      PDF（pc） （1310KB）（184）       Knowledge map    Save This paper presents a quantitative risk analysis of liquefied petroleum gas (LPG) transportation. An accident that happened on June 13, 2020, on the highway near Wenling, China is studied as a case. In this accident, LPG carried by a tank truck on the highway leaked and caused a large explosion, which led to 20 deaths. Different methods are combined to calculate the consequence of the accident. Multi-energy model and rupture of vessel model are employed to calculate the overpressure; the simulation result of the multi-energy model is closer to the damage caused by the accident. The safety distances in accidents of LPG transport storage tanks of different capacities are calculated in this study; the results show that the damage of explosion will increase with the filling degree of the tank. Even though the filling degree is 90% (value required by law), the 99% fatality rate range will reach 42 m, which is higher than regulated distance between road and building. The social risk of the tank truck has also been calculated and the results show that the risk is not acceptable. The calculating method used in this study could evaluate the risk of LPG tanker more accurately, which may contribute to the establishment of transportation regulation so that losses from similar accidents in the future could be reduced. Reference | Related Articles | Metrics | Comments（0）

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Anti-Occlusion Object Tracking Algorithm Based on Filter Prediction CHEN Kun(陈坤), ZHAO Xu(赵旭), DONG Chunyu(董春玉), DI Zichao(邸子超), CHEN Zongzhi(陈宗枝) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 400-413.   DOI: 10.1007/s12204-022-2484-8 Abstract （534）      PDF（pc） （5510KB）（180）       Knowledge map    Save Visual object tracking is an important issue that has received long-term attention in computer vision.The ability to effectively handle occlusion, especially severe occlusion, is an important aspect of evaluating theperformance of object tracking algorithms in long-term tracking, and is of great significance to improving therobustness of object tracking algorithms. However, most object tracking algorithms lack a processing mechanism specifically for occlusion. In the case of occlusion, due to the lack of target information, it is necessary to predict the target position based on the motion trajectory. Kalman filtering and particle filtering can effectively predict the target motion state based on the historical motion information. A single object tracking method, called probabilistic discriminative model prediction (PrDiMP), is based on the spatial attention mechanism in complex scenes and occlusions. In order to improve the performance of PrDiMP, Kalman filtering, particle filtering and linear filtering are introduced. First, for the occlusion situation, Kalman filtering and particle filtering are respectively introduced to predict the object position, thereby replacing the detection result of the original tracking algorithm and stopping recursion of target model. Second, for detection-jump problem of similar objects in complex scenes, a linear filtering window is added. The evaluation results on the three datasets, including GOT-10k, UAV123 and LaSOT, and the visualization results on several videos, show that our algorithms have improved tracking performance under occlusion and the detection-jump is effectively suppressed. Reference | Related Articles | Metrics | Comments（0）

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Ship Pipe Layout Optimization Based on Improved Particle Swarm Optimization LIN Yan1, 2(林焰), BIAN Xuanyi1(卞璇屹), DONG Zongran3(董宗然) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 737-746.   DOI: 10.1007/s12204-022-2530-6 Abstract （505）      PDF（pc） （1456KB）（180）       Knowledge map    Save Ship pipe layout optimization is one of the difficulties and hot spots in ship intelligent production design. A high-dimensional vector coding is proposed based on the research of related pipe coding and ship pipe route features in this paper. The advantages of this coding method are concise structure, strong compatibility, and independence from the gridding space. Based on the proposed coding, the particle swarm optimization algorithm is implemented, and the algorithm is improved by the pre-selected path strategy and the branch-pipe processing strategy. Finally, two simulation results reveal that the proposed coding and algorithm have feasibility and engineering practicability. Reference | Related Articles | Metrics | Comments（0）

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Performance Effect of Trench Casing on a Transonic Compressor at Different Rotating Speeds DENG Hefang (邓贺方), XIA Kailong (夏凯龙), TENG Jinfang (滕金芳), QIANG Xiaoqing (羌晓青), ZHU Mingmin∗ (朱铭敏), LU Shaopeng (卢少鹏) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1151-1160.   DOI: 10.1007/s12204-022-2541-3 Abstract （245）      PDF（pc） （2893KB）（175）       Knowledge map    Save The trench casing often occurs in axial compressors due to the casing rubbing or casing treatment. However, the effect of the trench casing on the aerodynamic performance of axial compressors has not been fully understood, especially at different rotating speeds. Therefore, we numerically investigate the effect of the trench casing on a transonic compressor at two rotating speeds. A detailed comparison of overall performance and flow characteristics has been performed. The results show that the trench configurations slightly increase the total pressure ratio and mass flow rate near the choking condition but reduce the total pressure ratio and adiabatic efficiency at small mass flow rates. The largest efficiency reduction of the parallel trench (PT) and within trench (IT) cases is more than 1%, which is located at the mid blade passage near 90% span. The effect of the trench configurations on the stall margin is different for the two rotating speeds. At 100% rotating speed, the outside trench (OT) and IT cases improve the stall margin by 2.8% and 1.1%, respectively, but the PT case decreases the stall margin by 1.3% due to the increased blockage in the core region of the tip leakage vortex. At 80% rotating speed, the stall margin of the trench configurations becomes worse. Because of the increased blockage of the mid blade passage, the PT and IT cases decrease the stall margin by 2.9% and 2.1%, respectively. Though there are some differences in the flow characteristics of the trench configurations at the two rotating speeds, the change of the stall margin always depends on the blockage near the tip region. This work can contribute to further understanding the impact of the trench casing on axial compressors. Reference | Related Articles | Metrics | Comments（0）

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Omnidirectional Human Behavior Recognition Method Based on Frequency-Modulated Continuous-Wave Radar Sun Chang, Wang Shaohong, Lin Yanping J Shanghai Jiaotong Univ Sci    2025, 30 (4): 637-645.   DOI: 10.1007/s12204-024-2580-z Abstract （130）      PDF（pc） （1094KB）（164）       Knowledge map    Save Frequency-modulated continuous-wave radar enables the non-contact and privacy-preserving recognition of human behavior. However, the accuracy of behavior recognition is directly influenced by the spatial relationship between human posture and the radar. To address the issue of low accuracy in behavior recognition when the human body is not directly facing the radar, a method combining local outlier factor with Doppler information is proposed for the correction of multi-classifier recognition results. Initially, the information such as distance, velocity, and micro-Doppler spectrogram of the target is obtained using the fast Fourier transform and histogram of oriented gradients - support vector machine methods, followed by preliminary recognition. Subsequently, Platt scaling is employed to transform recognition results into confidence scores, and finally, the Doppler - local outlier factor method is utilized to calibrate the confidence scores, with the highest confidence classifier result considered as the recognition outcome. Experimental results demonstrate that this approach achieves an average recognition accuracy of 96.23% for comprehensive human behavior recognition in various orientations. Reference | Related Articles | Metrics | Comments（0）

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Unsupervised Oral Endoscope Image Stitching Algorithm HUANG Rong (黄荣), CHANG Qing∗ (常青), ZHANG Yang （张扬） J Shanghai Jiaotong Univ Sci    2024, 29 (1): 81-90.   DOI: 10.1007/s12204-022-2513-7 Abstract （611）      PDF（pc） （5774KB）（164）       Knowledge map    Save Oral endoscope image stitching algorithm is studied to obtain wide-field oral images through registration and stitching, which is of great significance for auxiliary diagnosis. Compared with natural images, oral images have lower textures and fewer features. However, traditional feature-based image stitching methods rely heavily on feature extraction quality, often showing an unsatisfactory performance when stitching images with few features. Moreover, due to the hand-held shooting, there are large depth and perspective disparities between the captured images, which also pose a challenge to image stitching. To overcome the above problems, we propose an unsupervised oral endoscope image stitching algorithm based on the extraction of overlapping regions and the loss of deep features. In the registration stage, we extract the overlapping region of the input images by sketching polygon intersection for feature points screening and estimate homography from coarse to fine on a three-layer feature pyramid structure. Moreover, we calculate loss using deep features instead of pixel values to emphasize the importance of depth disparities in homography estimation. Finally, we reconstruct the stitched images from feature to pixel, which can eliminate artifacts caused by large parallax. Our method is compared with both feature-based and previous deep-based methods on the UDIS-D dataset and our oral endoscopy image dataset. The experimental results show that our algorithm can achieve higher homography estimation accuracy, and better visual quality, and can be effectively applied to oral endoscope image stitching. Reference | Related Articles | Metrics | Comments（0）

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New Encoder Based on Grating Eddy-Current with Differential Structure Zhang Zaiyi, Lv Na, Tao Wei, Zhao Hui J Shanghai Jiaotong Univ Sci    2025, 30 (2): 337-351.   DOI: 10.1007/s12204-023-2665-0 Abstract （248）      PDF（pc） （3147KB）（161）       Knowledge map    Save In response to the shortcomings of the common encoders in the industry, of which the photoelectric encoders have a poor anti-interference ability in harsh industrial environments with water, oil, dust, or strong vibrations and the magnetic encoders are too sensitive to magnetic field density, this paper designs a new differential encoder based on the grating eddy-current measurement principle, abbreviated as differential grating eddy-current encoder (DGECE). The grating eddy-current of DGECE consists of a circular array of trapezoidal reflection conductors and 16 trapezoidal coils with a special structure to form a differential relationship, which are respectively located on the code plate and the readout plate designed by a printed circuit board. The differential structure of DGECE corrects the common mode interference and the amplitude distortion due to the assembly to some extent, possesses a certain anti-interference capability, and greatly simplifies the regularization algorithm of the original data. By means of the corresponding readout circuit and demodulation algorithm, the DGECE can convert the periodic impedance variation of 16 coils into an angular output within the 360◦ cycle. Due to its simple manufacturing process and certain interference immunity, DGECE is easy to be integrated and mass-produced as well as applicable in the industrial spindles, especially in robot joints. This paper presents the measurement principle, implementation methods, and results of the experiment of the DGECE. The experimental results show that the accuracy of the DGECE can reach 0.237% and the measurement standard deviation can reach ±0.14 ◦ within 360 ◦ cycle. Reference | Related Articles | Metrics | Comments（0）

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Online Multi-Object Tracking Under Moving Unmanned Aerial Vehicle Platform Based on Object Detection and Feature Extraction Network LIU Zengmin (刘增敏), WANG Shentao(王申涛), YAO Lixiu(姚莉秀), CAI Yunze(蔡云泽) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 388-399.   DOI: 10.1007/s12204-022-2540-4 Abstract （395）      PDF（pc） （1105KB）（151）       Knowledge map    Save In order to solve the problem of small object size and low detection accuracy under the unmanned aerial vehicle (UAV) platform, the object detection algorithm based on deep aggregation network and high-resolution fusion module is studied. Furthermore, a joint network of object detection and feature extraction is studied to construct a real-time multi-object tracking algorithm. For the problem of object association failure caused by UAV movement, image registration is applied to multi-object tracking and a camera motion discrimination model is proposed to improve the speed of the multi-object tracking algorithm. The simulation results show that the algorithm proposed in this study can improve the accuracy of multi-object tracking under the UAV platform, and effectively solve the problem of association failure caused by UAV movement. Reference | Related Articles | Metrics | Comments（0）

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Flexural Behavior of Cross-Connected Brick Masonry Infill Wall Panels Supported on Reinforced Concrete Beam Grids BAYOUMI EL-Said Abd-Allah1, 2∗ , MAHMOUD Mahmoud Hassan3 , ARIF Mohammed 1, 4 J Shanghai Jiaotong Univ Sci    2024, 29 (5): 889-899.   DOI: 10.1007/s12204-022-2404-y Abstract （177）      PDF（pc） （3708KB）（150）       Knowledge map    Save This paper presents an experimental investigation on the flexural behavior of cross-connected brick masonry infill wall panels supported on reinforced concrete beam grids above and below the walls. The experimental program was comprised of six wall systems. The effect of change in lower beam stiffness relative to the wall and the geometry of the main walls were investigated. From the results of the experimental tests, the increase in the depth of the lower beam grid reduces the deflection, resulting in an increase in the load carrying capacity of the wall. Further, the stiffness of the main walls affects the deflection and the failure load of the cross walls. Reference | Related Articles | Metrics | Comments（0）

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Data Augmentation of Ship Wakes in SAR Images Based on Improved CycleGAN YAN Congqiang1,2 (鄢丛强), GUO Zhengyun3,4 (郭正玉), CAI Yunze1,2∗∗ (蔡云泽) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 702-711.   DOI: 10.1007/s12204-024-2746-8 Abstract （430）      PDF（pc） （1418KB）（149）       Knowledge map    Save The study on ship wakes of synthetic aperture radar (SAR) images holds great importance in detecting ship targets in the ocean. In this study, we focus on the issues of low quantity and insufficient diversity in ship wakes of SAR images, and propose a method of data augmentation of ship wakes in SAR images based on the improved cycle-consistent generative adversarial network (CycleGAN). The improvement measures mainly include two aspects: First, to enhance the quality of the generated images and guarantee a stable training process of the model, the least-squares loss is employed as the adversarial loss function; Second, the decoder of the generator is augmented with the convolutional block attention module (CBAM) to address the issue of missing details in the generated ship wakes of SAR images at the microscopic level. The experiment findings indicate that the improved CycleGAN model generates clearer ship wakes of SAR images, and outperforms the traditional CycleGAN models in both subjective and objective aspects. Reference | Related Articles | Metrics | Comments（0）

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Iterative Model Predictive Control for Automatic Carrier Landing of Carrier-Based Aircrafts Under Complex Surroundings and Constraints ZHANG Xiaotian1(张啸天), HE Defeng1* (何德峰), LIAO Fei2 (廖飞) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 712-724.   DOI: 10.1007/s12204-023-2690-z Abstract （384）      PDF（pc） （1363KB）（146）       Knowledge map    Save This paper considers the automatic carrier landing problem of carrier-based aircrafts subjected to constraints, deck motion, measurement noises, and unknown disturbances. The iterative model predictive control (MPC) strategy with constraints is proposed for automatic landing control of the aircraft. First, the long shortterm memory (LSTM) neural network is used to calculate the adaptive reference trajectories of the aircraft. Then the Sage-Husa adaptive Kalman filter and the disturbance observer are introduced to design the composite compensator. Second, an iterative optimization algorithm is presented to fast solve the receding horizon optimal control problem of MPC based on the Lagrange’s theory. Moreover, some sufficient conditions are derived to guarantee the stability of the landing system in a closed loop with the MPC. Finally, the simulation results of F/A-18A aircraft show that compared with the conventional MPC, the presented MPC strategy improves the computational efficiency by nearly 56% and satisfies the control performance requirements of carrier landing. Reference | Related Articles | Metrics | Comments（0）

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Multi-AGVs Scheduling with Vehicle Conflict Consideration in Ship Outfitting Items Warehouse CHEN Yini(陈旖旎), JIANG Zuhua* (蒋祖华) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 492-508.   DOI: 10.1007/s12204-022-2561-z Abstract （314）      PDF（pc） （1356KB）（146）       Knowledge map    Save The inbound and outbound tasks for valuable imported ship outfitting items are operated by multiple automated guided vehicles (AGVs) simultaneously in the outfitting warehouse. Given the efficiency mismatch between transportation equipment and the lack of effective scheduling of AGVs, the objective of the studied scheduling problem is to minimize the total travel time cost of vehicles. A multi-AGV task scheduling model based on time window is established considering the loading constraints of AGVs and cooperation time window constraints of stackers. According to the transportation characteristics in the outfitting warehouse, this study proposes a conflict detection method for heavy forklift AGVs, and correspondingly defines a conflict penalty function. Furthermore, to comprehensively optimize travel time cost and conflict penalty, a hybrid genetic neighborhood search algorithm (GA-ANS) is proposed. Five neighborhood structures are designed, and adaptive selection operators are introduced to enhance the ability of global search and local chemotaxis. Numerical experiments show that the proposed GA-ANS algorithm can effectively solve the problem even when the scale of the problem increases and the effectiveness of the vehicle conflict penalty strategy is analyzed. Reference | Related Articles | Metrics | Comments（0）

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Load Characteristics and Optimal Layout of Center and Gage Cutters of Rock Formation Compound Tunnel Boring Machine ZHANG Kangjian (张康健), HU Zhechuan (胡哲钏), ZHANG Zhiqiang (张志强) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 857-875.   DOI: 10.1007/s12204-022-2532-4 Abstract （251）      PDF（pc） （7928KB）（143）       Knowledge map    Save The cutter layout of a full-face tunnel boring machine (TBM) directly affects its tunneling efficiency. The revolving diameter of the center cutter is small, and the double-edged design results in its rock breaking mechanism and force characteristics being significantly different from those of the single-edged cutter. The gage cutter is installed on the transition arc of the cutterhead, and the installation inclination complicates its movement and force. In this paper, by taking sandstone as the research object, the composite rock breaking models of the center cutter group and the gage cutter group of a compound TBM are separately established based on the three-dimensional particle discrete element method. The numerical models are verified by comparing results with the full-scale rotary cutting laboratory test. From the view point of the force characteristics of a single cutter, the propagation of rock cracks between adjacent cutters, the overall mechanical properties of the cutterhead, the load characteristics and layout form of the double-edged center cutter, and the installation angle range of the gage cutter were studied. Results demonstrate that the use of a cross-shaped center cutter layout can reduce the force of a single cutter ring and the overall load of the cutterhead, which is conducive to TBM stability during tunneling. Therefore, it is recommended that a cross-shaped layout for the double-edged center cutter of a rock formation compound TBM should be used. To improve the stability and service life of the cutter, we recommend setting the installation angle of the innermost gage cutter of the rock formation compound TBM to about 9◦, and the installation angle of the outermost gage cutter should not exceed 70◦. Reference | Related Articles | Metrics | Comments（0）