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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 （1503）      PDF（pc） （1195KB）（586）       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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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 （1495）      PDF（pc） （1179KB）（1979）       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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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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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 （1183）      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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Progress in Force-Sensing Techniques for Surgical Robots GAO Hongyan1, 2(高红岩), AI Xiaojie1, 2(艾孝杰), SUN Zhenglong3(孙正隆), CHEN Weidong1, 2(陈卫东), GAO Anzhu1, 2(高安柱) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 370-381.   DOI: 10.1007/s12204-023-2607-x Abstract （1147）      PDF（pc） （1017KB）（313）       Knowledge map    Save Force sensing is vital for situational awareness and safe interaction during minimally invasive surgery. Consequently, surgical robots with integrated force-sensing techniques ensure precise and safe operations. Over the past few decades, there has been considerable progress in force-sensing techniques for surgical robots. This review summarizes the existing electrically- and optically-based force sensors for surgical robots, including piezoresistive, piezoelectric, capacitive, intensity/phase-modulated, and fiber Bragg gratings. Their principles, applications, advantages, and limitations are also discussed. Finally, we summarize our conclusions regarding state-of-the-art force-sensing technologies for surgical robotics. Reference | Related Articles | Metrics | Comments（0）

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Travel Intention of Electric Vehicle Sharing based on Theory of Multiple Motivations BAO Lewen (鲍乐雯), MIAO Rui, ∗ (苗 瑞), CHEN Zhihua (陈志华), ZHANG Bo (张 博), GUO Peng (郭 鹏), MA Yuze (马宇泽) J Shanghai Jiaotong Univ Sci    2023, 28 (1): 1-9.   DOI: 10.1007/s12204-023-2563-5 Abstract （866）      PDF（pc） （467KB）（266）       Knowledge map    Save Determining the travel intention of residents with shared electric vehicles (EVs) is significant for promoting the development of low-carbon transportation, considering that common problems such as high idle rate and lack of attractiveness still exist. To this end, a structural equation model (SEM) based on the theory of multiple motivations is proposed in this paper. First, the influencing motivations for EV sharing are divided into three categories: consumer-driven, program-driven, and enterprise-driven motivations. Then, the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire. Finally, an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention. The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention, compared to program-driven motivations with impact weights from ?0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06. In terms of consumer-driven motivations, the weight of green travel awareness is the highest. The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident, enterprise, and government. Reference | Related Articles | Metrics | Comments（0）

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Video-Based Detection of Epileptic Spasms in IESS: Modeling, Detection, and Evaluation DING Lihui1, 2(丁黎辉), FU Lijun1, 3 (付立军), YANG Guang4(杨光), WAN Lin4, 5 (万林), CHANG Zhijun7(常志军) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 1-9.   DOI: 10.1007/s12204-024-2789-x Abstract （787）      PDF（pc） （712KB）（113）       Knowledge map    Save Behavioral scoring based on clinical observations remains the gold standard for screening, diagnosing,and evaluating infantile epileptic spasm syndrome (IESS). The accurate identification of seizures is crucial for clinical diagnosis and assessment. In this study, we propose an innovative seizure detection method based on video feature recognition of patient spasms. To capture the temporal characteristics of the spasm behavior presented in the videos effectively, we incorporate asymmetric convolution and convolution–batch normalization–ReLU (CBR) modules. Specifically within the 3D-ResNet residual blocks, we split the larger convolutional kernels into two asymmetric 3D convolutional kernels. These kernels are connected in series to enhance the ability of the convolutional layers to extract key local features, both horizontally and vertically. In addition, we introduce a 3D convolutional block attention module to enhance the spatial correlations between video frame channels efficiently. To improve the generalization ability, we design a composite loss function that combines cross-entropy loss with triplet loss to balance the classification and similarity requirements. We train and evaluate our method using the PLA IESS-VIDEO dataset, achieving an average seizure recognition accuracy of 90.59%, precision of 90.94%, and recall of 87.64%. To validate its generalization capability further, we conducted external validation using six different patient monitoring videos compared with assessments by six human experts from various medical centers. The final test results demonstrate that our method achieved a recall of 0.647 6, surpassing the average level achieved by human experts (0.559 5), while attaining a high F1-score of 0.721 9. These findings have substantial significance for the long-term assessment of patients with IESS. Reference | Supplementary Material | Related Articles | Metrics | Comments（0）

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot ZHAO Yanfei1，2，3(赵艳飞), XIAO Peng4 (肖鹏), WANG Jingchuan1，2，3* (王景川), GUO Rui4*(郭锐） J Shanghai Jiaotong Univ Sci    2025, 30 (1): 27-33.   DOI: 10.1007/s12204-023-2678-8 Abstract （718）      PDF（pc） （996KB）（71）       Knowledge map    Save Mobile robots represented by smart wheelchairs can assist elderly people with mobility difficulties. This paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots, which can assist users to implement accurate navigation (e.g., docking) in the environment without prior maps. In order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms, this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic goals. At last, comparative experiments were carried out in the real environment. Results show that our method is superior in terms of safety, comfort and docking accuracy. Reference | Related Articles | Metrics | Comments（0）

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Physical Characterization of Ionic Liquid-Modified Polyvinyl Alcohol and Sodium Thiocyanate Polymer Electrolytes for Electrochemical Double-Layer Capacitor Application AZEMTSOP Manfo Theodore , MEHRA Ram Mohan , KUMAR Yogesh , GUPTA Meenal J Shanghai Jiaotong Univ Sci    2023, 28 (2): 161-171.   DOI: 10.1007/s12204-021-2397-y Abstract （686）      PDF（pc） （1140KB）（164）       Knowledge map    Save Novel gel polymer electrolytes (GPEs) composed of polyvinyl alcohol (PVA) and sodium thiocyanate were developed via a solution casting technique. An ionic liquid (IL), 1-ethyl-3-methyl-imidazolium tricyanomethanide ([EMIM][TCM]), was doped into a polymer–salt complex system (PVA + NaSCN) to further enhance the conductivity. IL-doped polymer electrolyte (ILDPE) films were characterized using X-ray diffraction (XRD), polarized optical microscopy (POM), Fourier-transform infrared (FTIR) spectroscopy, and conductivity measurements. XRD was performed to check the degree of crystallinity and amorphicity of the ILDPE films, and the amorphicity of GPEs increased with the increase of the IL content. POM was employed to evaluate the changes in the surface morphology due to the inclusion of salt and IL in the PVA. The compositional nature of the GPE films was examined via FTIR studies. The electrical and electrochemical properties were characterized by cyclic voltammetry and electrochemical impedance spectroscopy. The maximum conductivity for the GPE film was estimated to be 1.10 × 10-5 S/cm for 6% (mass fraction) of IL in the polymer–salt complex. The ionic transference number was approximately 0.97. An electrochemical double-layer capacitor (EDLC) was built from optimized GPE films and reduced graphene oxide-based electrodes. The specific capacitance calculated from the cyclic voltammograms of the EDLC cells was 3 F/g. Reference | Related Articles | Metrics | Comments（0）

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Integrated Hydraulic-Driven Wearable Robot for Knee Assistance ZHAO Yafei (赵亚飞), HUANG Chaoyi (黄超逸), ZOU Yuging(邹玉莹), ZOUKehan(邹可涵), zoU Xiaogang(邹笑阳), XUE .Jiaqi(薛嘉琦), LI Xiaoting(李晓婷), KOH Keng Huat, WANG Xiaojun(王小军), LAI Wai Chiu King(赖伟超), HU Yong(胡勇), XI Ning(席宁), WANG Zheng(王峥) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 289-295.   DOI: 10.1007/s12204-023-2602-2 Abstract （676）      PDF（pc） （1156KB）（226）       Knowledge map    Save Age-related diseases can lead to knee joint misfunction, making knee assistance necessary through the use of robotic wearable braces. However, existing wearable robots face challenges in force transmission and human motion adaptation, particularly among the elderly. Although soft actuators have been used in wearable robots, achieving rapid response and motion control while maintaining portability remains challenging. To address these issues, we propose a soft-robotic knee brace system integrated with multiple sensors and a direct-drive hydraulic actuation system. This approach allows for controlled and rapid force output on the portable hydraulic system. The multi-sensor feedback structure enables the robotic system to collaborate with the human body through human physiological signal and body motion information. The human user tests demonstrate that the knee robot provides assistive torques to the knee joint by being triggered by the electromyography signal and under human motion control. Reference | Related Articles | Metrics | Comments（0）

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Strength-Toughness Improvement of 15-5PH Stainless Steel by Double Aging Treatment TE Rigele (特日格乐), ZHANG Yutuo, ∗ (张玉妥) J Shanghai Jiaotong Univ Sci    2023, 28 (2): 270-279.   DOI: 10.1007/s12204-021-2390-5 Abstract （672）      PDF（pc） （3166KB）（123）       Knowledge map    Save To obtain better strength-toughness balance of 15-5PH stainless steel, a double aging treatment is proposed to investigate the mechanical properties and microstructure evolution. In this study, Cu precipitates and reversed austenite played a determining role to improve strength-toughness combination. The microstructure was observed using electron backscattered diffraction, transmission electron microscopy and scanning transmission electron microscopy. The volume fractions of Cu precipitates and reversed austenite were calculated with Thermo-Calc software and measured by X-ray diffraction. The results showed that the reversed austenite is formed at the martensitic lath boundaries and its volume fraction also increases with the increase of the aging temperature. At the same time, the size of the Cu precipitates gradually increases. Compared with the traditional single aging and double aging treatment, double aging treatment of 15-5PH stainless steel can increase the toughness while retaining the necessary strength. During double aging of 550 ℃ × 4 h + 580 ℃ × 1 h, 15-5PH stainless steel has the best strength and low-temperature (- 40 ℃) toughness match. Its yield strength, ultimate tensile strength and the Charpy impact energy are 1.037 GPa, 1.086 GPa and 179 J, respectively. Reference | Related Articles | Metrics | Comments（0）

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Intelligent Driving Assistance System for Safe Expressway Driving in Rainy and Foggy Weather based on IoT YAN Beirui (燕北瑞), FANG Cheng (方 成), QIU Hao (邱 昊), ZHU Wenfeng∗ (朱文峰) J Shanghai Jiaotong Univ Sci    2023, 28 (1): 10-19.   DOI: 10.1007/s12204-023-2564-4 Abstract （670）      PDF（pc） （2162KB）（152）       Knowledge map    Save The feature bends and tunnels of mountainous expressways are often affected by bad weather, specifically rain and fog, which significantly threaten expressway safety and traffic efficiency. In order to solve this problem, a vehicle–road coordination system based on the Internet of Things (IoT) is developed that can share vehicle–road information in real time, expand the environmental perception range of vehicles, and realize vehicle–road collaboration. It helps improve traffic safety and efficiency. Further, a vehicle–road cooperative driving assistance system model is introduced in this study, and it is based on IoT for improving the driving safety of mountainous expressways. Considering the influence of rain and fog on driving safety, the interaction between rainfall, water film, and adhesion coefficient is analyzed. An intelligent vehicle–road coordination assistance system is constructed that takes in information on weather, road parameters, and vehicle status, and takes the stopping sight distance model as well as rollover and sideslip model as boundary constraints. Tests conducted on a real expressway demonstrated that the assistance system model is helpful in bad weather conditions. This system could promote intelligent development of mountainous expressways. Reference | Related Articles | Metrics | Comments（0）

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Development of Rehabilitation and Assistive Robots in China: Dilemmas and Solutions ZHAO Lingling1*(赵玲玲),GUO Yao2(郭遥) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 382-390.   DOI: 10.1007/s12204-023-2596-9 Abstract （663）      PDF（pc） （367KB）（134）       Knowledge map    Save China is rapidly becoming an aging society, leading to a significant demand for chronic disease management and personalized healthcare. The development of rehabilitation and assistive robotics in China has gathered significant attention not only in research fields but also in industries. Such robots aim to either guide patients in completing therapeutic training or assist people with impaired functions in performing their daily activities. In the past decades, we have witnessed the advancement in rehabilitation and assistive robotics, with diverse mechanical designs, functionalities, and purposes. However, the construction of dedicated regulations and policies is relatively lagged compared with the flourishing development in research fields. Moreover, these kinds of robots are working or collaborating closely with human beings, bringing unprecedented considerations on ethical issues. This paper aims to provide an overview of major dilemmas in the development of rehabilitation and assistive robotics in China and propose several potential solutions. Reference | Related Articles | Metrics | Comments（0）

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Design of Twin-Screw Compressor Rotor Tooth Profile with Meshing Clearance Based on Graphic Method and Alpha Shape Algorithm YANG Jian, ∗ (杨 剑), XU Mingzhao (徐明照), LU Zheng (陆 征) J Shanghai Jiaotong Univ Sci    2023, 28 (2): 243-254.   DOI: 10.1007/s12204-021-2396-z Abstract （652）      PDF（pc） （1955KB）（139）       Knowledge map    Save Rotor clearance is necessary for the safe operation of twin-screw compressors, and it has a major impact on the performance of twin-screw compressors. The purpose of this study was to obtain a rotor tooth profile with reasonable meshing clearance on the rotor end surface, so that the clearance on the rotor contact line would be uniform and the rotor could be smoothly meshed. Under ideal conditions, the rotor of a screw compressor should have no clearance or interference. However, owing to assembly errors, thermal compression, stress deformation, and other factors, a rotor without backlash modification will inevitably produce interference during operation. A new design method based on the Alpha shape solution was proposed to achieve an efficient and high-precision design of the clearance of the twin-screw rotor profile. This method avoids the complex analytical calculations in the traditional envelope principle. The best approximation of the points on the rotor conjugate motion sweeping surface in the points is illuminated using a specific color. The sweeping surface of the screw rotor single-tooth profile is roughly scanned to capture the base point set of the sweeping surface boundary points. The chord length and tilt angle of each interval are calculated using the value of the base point set to adjust the position, phase, and magnification of each interval sweeping surface. Finally, the data point set is converted to the same coordinate system to generate the conjugated rotor profile. An example was used to verify the feasibility and adaptability of this method. Based on the equidistant profile method, the clearance between male and female rotors of a screw compressor was obtained under actual operation conditions. Therefore, this study provides a basis for the meshing clearance design in the machining of twin-screw compressor rotors. Reference | Related Articles | Metrics | Comments（0）

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Shape Sensing for Single-Port Continuum Surgical Robot Using Few Multicore Fiber Bragg Grating Sensors LI Dingjia1,2,3,4(黎定佳)，WANG Chongang1,2,3(王重阳)，GUO Wei5(郭伟)，WANG Zhidong6(王志东)，ZHANG Zhongtao5(张忠涛)，LIU Hao1,2,3*(刘浩) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 312-322.   DOI: 10.1007/s12204-023-2579-x Abstract （647）      PDF（pc） （2606KB）（117）       Knowledge map    Save We proposed a method for shape sensing using a few multicore fiber Bragg grating (FBG) sensors in a single-port continuum surgical robot (CSR). The traditional method of utilizing a forward kinematic model to calculate the shape of a single-port CSR is limited by the accuracy of the model. If FBG sensors are used for shape sensing, their accuracy will be affected by their number, especially in long and flexible CSRs. A fusion method based on an extended Kalman filter (EKF) was proposed to solve this problem. Shape reconstruction was performed using the CSR forward kinematic model and FBG sensors, and the two results were fused using an EKF. The CSR reconstruction method adopted the incremental form of the forward kinematic model, while the FBG sensor method adopted the discrete arc-segment assumption method. The fusion method can eliminate the inaccuracy of the kinematic model and obtain more accurate shape reconstruction results using only a small number of FBG sensors. We validated our algorithm through experiments on multiple bending shapes under different load conditions. The results show that our method significantly outperformed the traditional methods in terms of robustness and effectiveness. Reference | Related Articles | Metrics | Comments（0）

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Action-aware Encoder-Decoder Network for Pedestrian Trajectory Prediction FU Jiawei∗ (傅家威), ZHAO Xu (赵 旭) J Shanghai Jiaotong Univ Sci    2023, 28 (1): 20-27.   DOI: 10.1007/s12204-023-2565-3 Abstract （633）      PDF（pc） （775KB）（173）       Knowledge map    Save Accurate pedestrian trajectory predictions are critical in self-driving systems, as they are fundamental to the response- and decision-making of ego vehicles. In this study, we focus on the problem of predicting the future trajectory of pedestrians from a first-person perspective. Most existing trajectory prediction methods from the first-person view copy the bird’s-eye view, neglecting the differences between the two. To this end, we clarify the differences between the two views and highlight the importance of action-aware trajectory prediction in the first-person view. We propose a new action-aware network based on an encoder-decoder framework with an action prediction and a goal estimation branch at the end of the encoder. In the decoder part, bidirectional long short-term memory (Bi-LSTM) blocks are adopted to generate the ultimate prediction of pedestrians’ future trajectories. Our method was evaluated on a public dataset and achieved a competitive performance, compared with other approaches. An ablation study demonstrates the effectiveness of the action prediction branch. Reference | Related Articles | Metrics | Comments（0）

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Foreground Segmentation Network with Enhanced Attention JIANG Rui1*(姜﹐锐)，ZHU Ruiriang1(朱瑞祥)，CAI Xiaocui1(蔡萧萃)，SU Hu2(苏虎) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 360-369.   DOI: 10.1007/s12204-023-2603-1 Abstract （631）      PDF（pc） （734KB）（93）       Knowledge map    Save Moving object segmentation (MOS) is one of the essential functions of the vision system of all robots,including medical robots. Deep learning-based MOS methods, especially deep end-to-end MOS methods, are actively investigated in this field. Foreground segmentation networks (FgSegNets) are representative deep end-to-end MOS methods proposed recently. This study explores a new mechanism to improve the spatial feature learning capability of FgSegNets with relatively few brought parameters. Specifically, we propose an enhanced attention (EA) module, a parallel connection of an attention module and a lightweight enhancement module, with sequential attention and residual attention as special cases. We also propose integrating EA with FgSegNet v2 by taking the lightweight convolutional block attention module as the attention module and plugging EA module after the two Maxpooling layers of the encoder. The derived new model is named FgSegNet v2 EA. The ablation study verifies the effectiveness of the proposed EA module and integration strategy. The results on the CDnet2014 dataset, which depicts human activities and vehicles captured in different scenes, show that FgSegNet v2 EA outperforms FgSegNet v2 by 0.08% and 14.5% under the settings of scene dependent evaluation and scene independent evaluation, respectively, which indicates the positive effect of EA on improving spatial feature learning capability of FgSegNet v2. Reference | Related Articles | Metrics | Comments（0）

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Boosting Unsupervised Domain Adaptation with Soft Pseudo-Label and Curriculum Learning ZHANG Shengjia(张晟嘉), LIN Tiancheng(林天成), XU Yi(徐奕) J Shanghai Jiaotong Univ Sci    2023, 28 (6): 703-716.   DOI: 10.1007/s12204-022-2487-5 Abstract （629）      PDF（pc） （963KB）（178）       Knowledge map    Save By leveraging data from a fully labeled source domain, unsupervised domain adaptation (UDA) improves classification performance on an unlabeled target domain through explicit discrepancy minimization of data distribution or adversarial learning. As an enhancement, category alignment is involved during adaptation to reinforce target feature discrimination by utilizing model prediction. However, there remain unexplored problems about pseudo-label inaccuracy incurred by wrong category predictions on target domain, and distribution deviation caused by overfitting on source domain. In this paper, we propose a model-agnostic two-stage learning framework, which greatly reduces flawed model predictions using soft pseudo-label strategy and avoids overfitting on source domain with a curriculum learning strategy. Theoretically, it successfully decreases the combined risk in the upper bound of expected error on the target domain. In the first stage, we train a model with distribution alignment-based UDA method to obtain soft semantic label on target domain with rather high confidence. To avoid overfitting on source domain, in the second stage, we propose a curriculum learning strategy to adaptively control the weighting between losses from the two domains so that the focus of the training stage is gradually shifted from source distribution to target distribution with prediction confidence boosted on the target domain. Extensive experiments on two well-known benchmark datasets validate the universal effectiveness of our proposed framework on promoting the performance of the top-ranked UDA algorithms and demonstrate its consistent superior performance. Reference | Related Articles | Metrics | Comments（0）

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Lidar-Visual-Inertial Odometry with Online Extrinsic Calibration MAO Tianyang (茅天阳), ZHAO Wentao (赵文韬), WANG Jingchuan∗ (王景川), CHEN Weidong (陈卫东) J Shanghai Jiaotong Univ Sci    2023, 28 (1): 70-76.   DOI: 10.1007/s12204-023-2570-6 Abstract （619）      PDF（pc） （988KB）（155）       Knowledge map    Save To achieve precise localization, autonomous vehicles usually rely on a multi-sensor perception system surrounding the mobile platform. Calibration is a time-consuming process, and mechanical distortion will cause extrinsic calibration errors. Therefore, we propose a lidar-visual-inertial odometry, which is combined with an adapted sliding window mechanism and allows for online nonlinear optimization and extrinsic calibration. In the adapted sliding window mechanism, spatial-temporal alignment is performed to manage measurements arriving at different frequencies. In nonlinear optimization with online calibration, visual features, cloud features, and inertial measurement unit (IMU) measurements are used to estimate the ego-motion and perform extrinsic calibration. Extensive experiments were carried out on both public datasets and real-world scenarios. Results indicate that the proposed system outperforms state-of-the-art open-source methods when facing challenging sensor-degenerating conditions. 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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Novel Concentric Tube Robot Based on Double-Threaded Helical Gear Tube CHEN Weichi(陈韦池), LIU Haocheng(刘浩城), LI Zijian(李子建), GUO Jing, (郭靖), ZHAI Zhenkun(翟振坤), MENG Wei(孟伟) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 296-306.   DOI: 10.1007/s12204-023-2595-x Abstract （604）      PDF（pc） （2087KB）（152）       Knowledge map    Save Nasopharyngeal carcinoma is a malignant tumor originating from the nasal mucosa. It is a malignant tumor of the head and neck. Concentric tube robot (CTR), as it can form a complicated shape and access hardto-reach lesions, is often used in minimally invasive surgeries. However, some CTRs are bulky because of their transmission design. In this paper, a light CTR based on double-threaded helical gear tube is proposed. Such a CTR is less cumbersome than the traditional CTR as its actuation unit is compact and miniaturized. The mapping relationship between the gear tube attitude and motor output angle is obtained by kinematic analysis. The precision, stability, and repeatability of the driving mechanism are tested. The experimental results show that the positioning error in the translation test is less than 0.3 mm, the rolling angle error in the stability test is less than 0.6?, and the error in the translation repeatability test is less than 0.005 mm. Finally, a tip-targeting test is performed using the new CTR, which verifies the feasibility of the CTR for surgeries. Reference | Related Articles | Metrics | Comments（0）

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Numerical Study on Separation of Circulating Tumor Cell Using Dielectrophoresis in a Four-Electrode Microfluidic Device WANG Yukuna (王雨坤), DING Xiantingb (丁显廷), ZHANG Zhinana (张执南) J Shanghai Jiaotong Univ Sci    2023, 28 (4): 391-.   DOI: 10.1007/s12204-022-2459-9 Abstract （599）      PDF（pc） （1462KB）（493）       Knowledge map    Save This numerical study proposes a cell sorting technique based on dielectrophoresis (DEP) in a microfluidic chip. Under the joint effect of DEP and fluid drag, white blood cells and circulating tumor cells are separated because of different dielectric properties. First, the mathematical models of device geometry, single cell, DEP force, electric field, and flow field are established to simulate the cell motion. Based on the simulation model, important boundary parameters are discussed to optimize the cell sorting ability of the device. A proper matching relationship between voltage and flow rate is then provided. The inlet and outlet conditions are also investigated to control the particle motion in the flow field. The significance of this study is to verify the cell separating ability of the microfluidic chip, and to provide a logistic design for the separation of rare diseased cells. 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）（809）       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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Entity Relationship Explanation via Conceptualization XIE Chenhao(谢晨昊), LIANG Jiaqing(梁家卿), XIA Yanghua(肖仰华), HWANG Seung-won J Shanghai Jiaotong Univ Sci    2023, 28 (6): 695-702.   DOI: 10.1007/s12204-021-2394-1 Abstract （592）      PDF（pc） （608KB）（165）       Knowledge map    Save Finding an attribute to explain the relationships between a given pair of entities is valuable in many applications. However, many direct solutions fail, owing to its low precision caused by heavy dependence on text and low recall by evidence scarcity. Thus, we propose a generalization-and-inference framework and implement it to build a system: entity-relationship finder (ERF). Our main idea is conceptualizing entity pairs into proper concept pairs, as intermediate random variables to form the explanation. Although entity conceptualization has been studied, it has new challenges of collective optimization for multiple relationship instances, joint optimization for both entities, and aggregation of diluted observations into the head concepts defining the relationship. We propose conceptualization solutions and validate them as well as the framework with extensive experiments. Reference | Related Articles | Metrics | Comments（0）

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Electric vehicle charging situation awareness for charging station ultra-short-term load forecast SHI Yiwei1 (史一炜), LIU Zeyu1 (刘泽宇), FENG Donghan1∗ (冯冬涵), ZHOU Yun1∗ (周 云), ZHANG Kaiyu2 (张开宇), LI Hengjie3 (李恒杰) J Shanghai Jiaotong Univ Sci    2023, 28 (1): 28-38.   DOI: 10.1007/s12204-023-2566-2 Abstract （589）      PDF（pc） （1518KB）（1429）       Knowledge map    Save Electric vehicles (EVs) are expected to be key nodes connecting transportation–electricity–communication networks. Advanced automotive electronics technologies enhance EVs’ perception, computing, and communication capacity, which in turn can boost the operational efficiency of intelligent transportation systems (ITSs). EVs couple the ITS to the power system, providing a promising solution to charging congestion and transformer overload via navigation and forecasting approaches. This study proposes a privacy-preserving EV charging situation awareness framework and method to forecast the ultra-short-term load of charging stations. The proposed method only relies on public information from commercial service providers. In the case study, data are powered by the Baidu LBS cloud and EV-SGCC platform, and the experiment is conducted within an area of Pudong New District in Shanghai. Based on the results, the charging load of charging stations can be adequately forecasted more than 1 min ahead with low communication and computing power requirements. This research provides the basis for further studies on operation optimization and electricity market transaction of charging stations. Reference | Related Articles | Metrics | Comments（0）

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Early Detection Methods of Deep Tissue Pressure Injuries: A Systematic Review JIA Jingyil (贾菁怡)，LI Zhengyi1,2 (李正裔)，PENG Linjing1 (彭琳晶)，YAO Yifeil* (姚怡飞) J Shanghai Jiaotong Univ Sci    2023, 28 (4): 526-.   DOI: 10.1007/s12204-022-2518-2 Abstract （578）      PDF（pc） （552KB）（239）       Knowledge map    Save Deep tissue pressure injuries (DTPIs) have witnessed a growing prevalence in hospitals and other health care units especially among individuals with pathological conditions that give rise to restricted mobility, impaired sensation, and reduced tissue tolerance. The etiology of DTPIs has been a subject of controversy, to which several explanatory models have been proposed, including direct mechanical insult, ischemia-reperfusion, lymphatic occlusion, and inflammatory cytokines. In line with these pathophysiological scenarios, ultrasound, subepidermal moisture detection, and biomarker technologies have been proposed as potential early detection methods of DTPIs. This paper provides a systematic review involving these three methods. The conclusion is that combining and implementing these methods at different time periods during DTPIs development and progression respectively is likely to be the most universal, effective and promising way for DTPIs diagnosis. Reference | Related Articles | Metrics | Comments（0）

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Applications of Artificial Intelligence in Cardiac Electrophysiology and Clinical Diagnosis with Magnetic Resonance Imaging and Computational Modeling Techniques ZHAN Heqing1 (詹何庆), HAN Guilai1 (韩贵来), WEI Chuan’an1 (魏传安), LI Zhiqun2* (李治群) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 53-65.   DOI: 10.1007/s12204-023-2628-5 Abstract （573）      PDF（pc） （233KB）（75）       Knowledge map    Save The underlying electrophysiological mechanisms and clinical treatments of cardiovascular diseases, which are the most common cause of morbidity and mortality worldwide, have gotten a lot of attention and been widely explored in recent decades. Along the way, techniques such as medical imaging, computing modeling, and artificial intelligence (AI) have always played significant roles in above studies. In this article, we illustrated the applications of AI in cardiac electrophysiological research and disease prediction. We summarized general principles of AI and then focused on the roles of AI in cardiac basic and clinical studies incorporating magnetic resonance imaging and computing modeling techniques. The main challenges and perspectives were also analyzed. Reference | Related Articles | Metrics | Comments（0）

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Stagewise Training for Hybrid-Distorted Image Restoration HOU Shujuan* (侯舒娟)，ZHU Wenping (朱文萍)，LI Hai (李海) J Shanghai Jiaotong Univ Sci    2023, 28 (6): 793-801.   DOI: 10.1007/s12204-022-2453-2 Abstract （554）      PDF（pc） （1221KB）（170）       Knowledge map    Save Image restoration is the problem of restoring a real degraded image. Previous studies mostly focused on single distortion. However, most of the real images experience multiple distortions, and single distortion image restoration algorithms can not effectively improve the image quality. Moreover, few existing hybrid distortion image restoration algorithms can not deal with single distortion. Therefore, an end-to-end pipeline network based on stagewise training is proposed in this paper. Specifically, the network selects three typical image restoration tasks: denoising, inpainting, and super resolution. The whole training process is divided into single distortion training, hybrid distortion training of two types, and hybrid distortion training of three types. The design of loss function draws on the idea of deep supervision. Experimental results prove that the proposed method is not only superior to other methods in hybrid-distorted image restoration, but also suitable for single distortion image restoration. Reference | Related Articles | Metrics | Comments（0）

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Synthesis and Characterization of Copper Doped Zinc Oxide Thin Films Deposited by RF/DC Sputtering Technique KHAN Mohibul, ALAM Md. Shabaz, AHMED Sk. Faruque∗ J Shanghai Jiaotong Univ Sci    2023, 28 (2): 172-179.   DOI: 10.1007/s12204-022-2462-1 Abstract （544）      PDF（pc） （698KB）（106）       Knowledge map    Save Undoped and copper (Cu) doped zinc oxide (Zn1-xCuxO, where x = 0—0.065) nano crystal thin films have been deposited on glass substrate via RF/DC reactive co-sputtering technique. The aim of this work is to investigate the crystal structure of ZnO and Cu doped ZnO thin films and also study the effect of Cu doping on optical band gap of ZnO thin films. The identification and confirmation of the crystallinity, film thickness and surface morphology of the nano range thin films are confirmed by using X-ray diffractometer (XRD), scanning electron microscope and atomic force microscope. The XRD peak at a diffractive angle of 34.44° and Miller indices at (002) confirms the ZnO thin films. Crystallite size of undoped ZnO thin films is 27 nm and decreases from 27 nm to 22 nm with increasing the atomic fraction of Cu (xCu) in the ZnO thin films from 0 to 6.5% respectively, which is calculated from XRD (002) peaks. The different bonding information of all deposited films was investigated by Fourier transform infrared spectrometer in the range of wave number between 400 cm-1 to 4 000 cm-1. Optical band gap energy of all deposited thin films was analyzed by ultraviolet visible spectrophotometer, which varies from 3.35 eV to 3.19 eV with the increase of xCu from 0 to 6.5% respectively. Urbach energy of the deposited thin films increases from 115 meV to 228 meV with the increase of xCu from 0 to 6.5% respectively. 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）（181）       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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Time-Resolved Imaging in Short-Wave Infrared Region XU Yang (徐杨), LI Wanwan∗ (李万万) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 29-36.   DOI: 10.1007/s12204-022-2547-x Abstract （533）      PDF（pc） （810KB）（134）       Knowledge map    Save Compared with the conventional first near-infrared (NIR-I, 700—900 nm) window, the short-wave infrared region (SWIR, 900—1 700 nm) possesses the merits of the increasing tissue penetration depths and the suppression of scattering background, leading to great potential for in vivo imaging. Based on the limitations of the common spectral domain, and the superiority of the time-dimension, time-resolved imaging eliminates the auto-fluorescence in the biological tissue, thus supporting higher signal-to-noise ratio and sensitivities. The imaging technique is not affected by the difference in tissue composition or thickness and has the practical value of quantitative in vivo detection. Almost all the relevant time-resolved imaging was carried out around lanthanide-doped upconversion nanomaterials, owing to the advantages of ultralong luminescence lifetime, excellent photostability, controllable morphology, easy surface modification and various strategies of regulating lifetime. Therefore, this review presents the research progress of SWIR time-resolved imaging technology based on nanomaterials doped with lanthanide ions as luminescence centers in recent years. 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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Medicine-Engineering Interdisciplinary Research Based on Bibliometric Analysis: A Case Study on Medicine-Engineering Institutional Cooperation of Shanghai Jiao Tong University WANG Qingwen (王庆稳)，CUI Tingting (崔婷婷)，DENG Peiwen* (邓珮雯) J Shanghai Jiaotong Univ Sci    2023, 28 (6): 841-856.   DOI: 10.1007/s12204-022-2418-5 Abstract （529）      PDF（pc） （1829KB）（1555）       Knowledge map    Save This article aims to provide reference for medicine-engineering interdisciplinary research. Targeted at the scientific literature and patent literature published by Shanghai Jiao Tong University, this article attempts to set up co-occurrence matrix of medicine-engineering institutional information which was extracted from address fields of the papers, so as to construct the medicine-engineering intersection datasets. The dataset of scientific literature was analyzed using bibliometrics and visualization methods from multiple dimensions, and the most active factors, such as trends of output, journal and subject distribution, were identified from the indicators of category normalized citation impact (CNCI), times cited, keywords, citation topics and the degree of medicineengineering interdisplinary. Research on hotspots and trends was discussed in detail. Analyses of the dataset of patent literature showed research themes and measured the degree for technology convergence of medicineengineering. Reference | Related Articles | Metrics | Comments（0）

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Federated Approach for Privacy-Preserving Traffic Prediction Using Graph Convolutional Network LONARE Savita1，2* , BHRAMARAMBA Ravi2 J Shanghai Jiaotong Univ Sci    2024, 29 (3): 509-517.   DOI: 10.1007/s12204-021-2382-5 Abstract （522）      PDF（pc） （525KB）（101）       Knowledge map    Save Existing traffic flow prediction frameworks have already achieved enormous success due to large traffic datasets and capability of deep learning models. However, data privacy and security are always a challenge in every field where data need to be uploaded to the cloud. Federated learning (FL) is an emerging trend for distributed training of data. The primary goal of FL is to train an efficient communication model without compromising data privacy. The traffic data have a robust spatio-temporal correlation, but various approaches proposed earlier have not considered spatial correlation of the traffic data. This paper presents FL-based traffic flow prediction with spatio-temporal correlation. This work uses a differential privacy (DP) scheme for privacy preservation of participant’s data. To the best of our knowledge, this is the first time that FL is used for vehicular traffic prediction while considering the spatio-temporal correlation of traffic data with DP preservation. The proposed framework trains the data locally at the client-side with DP. It then uses the model aggregation mechanism federated graph convolutional network (FedGCN) at the server-side to find the average of locally trained models. The results of the proposed work show that the FedGCN model accurately predicts the traffic. DP scheme at client-side helps clients to set a budget for privacy loss. Reference | Related Articles | Metrics | Comments（0）

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Safety Evaluation of Commercial Vehicle Driving Behavior Based on AHP-CRITIC Algorithm PANG Na1 (庞 娜), LUO Wenguang1∗ (罗文广), WU Ruoyuan1 (吴若园), LAN Hongli1 (蓝红莉), QIN Yongxin1 (覃永新), SU Qi2 (苏 琦) J Shanghai Jiaotong Univ Sci    2023, 28 (1): 126-135.   DOI: 10.1007/s12204-023-2575-1 Abstract （522）      PDF（pc） （421KB）（129）       Knowledge map    Save To prevent and reduce road traffic accidents and improve driver safety awareness and bad driving behaviors, we propose a safety evaluation method for commercial vehicle driving behavior. Three driving style classification indexes were extracted using driving data from commercial vehicles and four primary and ten secondary safety evaluation indicators. Based on the stability of commercial vehicles transporting goods, the acceleration index is divided into three levels according to the statistical third quartile, and the evaluation expression of the safety index evaluation is established. Drivers were divided into conservative, moderate, and radical using Kmeans++. The weights corresponding to each index were calculated using a combination of the analytic hierarchy process (AHP) and criteria importance through intercriteria correlation (CRITIC), and the driving behavior scores of various drivers were calculated according to the safety index score standard. The established AHP–CRITIC safety evaluation model was verified using the actual driving behavior data of commercial vehicle drivers. The calculation results show that the proposed evaluation model can clearly distinguish between the types of drivers with different driving styles, verifying its rationality and validity. The evaluation results can provide a reference for transportation management departments and enterprises. Reference | Related Articles | Metrics | Comments（0）

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Significant Retest Effects in Spatial Working Memory Task MA Xianda1,2,3‡ (马显达), LAN Zhaohui1,2,3‡ (兰兆辉),CHEN Zhitang1,2,3 (陈志堂), MONISHA M L4, HE Xinyi1,2,3 (何欣怡), LI Weidong1,2,3* (李卫东) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 115-120.   DOI: 10.1007/s12204-023-2585-z Abstract （518）      PDF（pc） （567KB）（50）       Knowledge map    Save Working memory is a core cognitive function that supports goal-directed behavior and complex thought. We developed a spatial working memory and attention test on paired symbols (SWAPS) which has been proved to be a useful and valid tool for spatial working memory and attention studies in the fields of cognitive psychology, education, and psychiatry. The repeated administration of working memory capacity tests is common in clinical and research settings. Studies suggest that repeated cognitive tests may improve the performance scores also known as retest effects. The systematic investigation of retest effects in SWAPS is critical for interpreting scientific results, but it is still not fully developed. To address this, we recruited 77 college students aged 18—21 years and used SWAPS comprising 72 trials with different memory loads, learning time, and delay span. We repeated the test once a week for five weeks to investigate the retest effects of SWAPS. There were significant retest effects in the first two tests: the accuracy of the SWAPS tests significantly increased, and then stabilized. These findings provide useful information for researchers to appropriately use or interpret the repeated working memory tests. Further experiments are still needed to clarify the factors that mediate the retest effects, and find out the cognitive mechanism that influences the retest effects. 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 （512）      PDF（pc） （2939KB）（701）       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）（596）       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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Calibration Technology of Optical Fiber Strain Sensor CHEN Gang(陈刚), LIU Hongyue(刘宏月), GAO Ruiriang(高瑞翔) J Shanghai Jiaotong Univ Sci    2023, 28 (5): 551-559.   DOI: 10.1007/s12204-022-2406-9 Abstract （509）      PDF（pc） （1122KB）（246）       Knowledge map    Save As one of the hotspots of sensing technology at present, optical fiber sensor has the characteristics of small size, anti-electromagnetic interference, and easy networking, which plays an irreplaceable role in multiphysics parameter monitoring of complex electromagnetic environments. The precise calibration of the optical fiber strain sensor has great practical value in prolonging the survival rate of the sensor, improving the measurement accuracy, and meeting the needs of long-term monitoring. By reviewing the research status of strain sensor calibration method and fiber optic strain sensor calibration method, the advantages and disadvantages of the main methods are analyzed separately from the static and dynamic perspectives, and the development prospect of the calibration technology of optic fiber strain sensor is summarized. 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）（182）       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）