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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 （359）      PDF（pc） （2836KB）（113）       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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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 （403）      PDF（pc） （1456KB）（109）       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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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 （213）      PDF（pc） （859KB）（87）       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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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 （254）      PDF（pc） （1725KB）（72）       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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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 （144）      PDF（pc） （1691KB）（63）       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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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 （566）      PDF（pc） （712KB）（63）       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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Experimental Study and Numerical Simulation of Evacuation in an Offshore Platform ZHANG Jingjinga (张菁菁), ZHAO Jinchenga, b, c∗(赵金城), SONG Zhensena, b, c (宋振森), DUAN Lipinga, b, c(段立平) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 747-758.   DOI: 10.1007/s12204-023-2629-4 Abstract （310）      PDF（pc） （4007KB）（50）       Knowledge map    Save With the rapid development of marine oil and gas exploitation, the evacuation of offshore platforms has received more attention. First, an experimental investigation of the evacuation process of 120 participants in a real offshore platform is performed, and then simulation results provided by Pathfinder are validated against the measurement results. Second, four typical evacuation scenarios on the platform referring to IMO guidelines are investigated by Pathfinder with the speed values achieved in experiments. The simulation results show that both the utilization of exits and evacuation efficiency of people on the offshore platform need to be further improved. Last, the evacuation routes of people under the four scenarios are optimized, and the improvement of the evacuation performance after the optimization is evaluated by several mathematical indicators. Final results show that the evacuation with the optimized route design prompts the use efficiency of exits and further reduces the evacuation time. The present study provides a useful advice for potentially revising the IMO guidelines in future and provides efficient evacuation strategies for planning the emergency evacuation on offshore platforms. 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 （161）      PDF（pc） （914KB）（49）       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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Augmented Reality Navigation Using Surgical Guides Versus Conventional Techniques in Pedicle Screw Placement KONG Huiyang1 (孔会扬), WANG Shuyi1 (王殊轶), ZHANG Can2 (张璨), CHEN Zan2, 3 (陈赞) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 10-17.   DOI: 10.1007/s12204-023-2689-5 Abstract （416）      PDF（pc） （1106KB）（40）       Knowledge map    Save The aim of this study was to assess the potential of surgical guides as a complementary tool to augmented reality (AR) in enhancing the safety and precision of pedicle screw placement in spinal surgery. Four trainers were divided into the AR navigation group using surgical guides and the free-hand group. Each group consisted of a novice and an experienced spine surgeon. A total of 80 pedicle screws were implanted. First, the AR group reconstructed the 3D model and planned the screw insertion route according to the computed tomography data of L2 lumbar vertebrae. Then, the Microsoft HoloLensTM 2 was used to identify the vertebral model, and the planned virtual path was superimposed on the real cone model. Next, the screw was placed according to the projected trajectory. Finally, Micron Tracker was used to measure the deviation of screws from the preoperatively planned trajectory, and pedicle screws were evaluated using the Gertzbein-Robbins scale. In the AR group, the linear deviations of the experienced doctor and the novice were (1.59±0.39) mm and (1.73±0.52) mm respectively, and the angle deviations were 2.72◦ ± 0.61◦ and 2.87◦ ± 0.63◦ respectively. In the free-hand group, the linear deviations of the experienced doctor and the novice were (2.88 ± 0.58) mm and (5.25 ± 0.62) mm respectively, and the angle deviations were 4.41◦ ± 1.18◦ and 7.15◦ ± 1.45◦ respectively. Both kinds of deviations between the two groups were significantly different (P < 0.05). The screw accuracy rate was 95% in the AR navigation group and 77.5% in the free-hand group. The results of this study indicate that the integration of surgical guides and AR is an innovative technique that can substantially enhance the safety and precision of spinal surgery and assist inexperienced doctors in completing the surgery. Reference | Related Articles | Metrics | Comments（0）

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Self-Tuning of MPC Controller for Mobile Robot Path Tracking Based on Machine Learning LIU Yuesheng (刘月笙), HE Ning∗ (贺宁), HE Lile (贺利乐), ZHANG Yiwen (张译文), XI Kun (习坤), ZHANG Mengrui (张梦芮) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1028-1036.   DOI: 10.1007/s12204-022-2545-z Abstract （281）      PDF（pc） （920KB）（38）       Knowledge map    Save Model predictive control (MPC) is a model-based optimal control strategy widely used in robot systems.In this work, the MPC controller tuning problem for the path tracking of the wheeled mobile robot is studied and a novel self-tuning approach is developed. First, two novel path tracking performance indices, i.e., steadystate time ratio and steady-state distance ratio are proposed to more accurately reflect the control performance.Second, the mapping relationship between the proposed indices and the MPC parameters is established based on machine learning technique, and then a novel controller structure which can automatically tune the control parameters online is further designed. Finally, experimental verification with an actual wheeled mobile robot is conducted, which shows that the proposed method could outperform the existing method via achieving significant improvement in the rapidity, accuracy and adaptability of the robot path tracking. Reference | Related Articles | Metrics | Comments（0）

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Comfort of Autonomous Vehicles Incorporating Quantitative Indices for Passenger Feeling PENG Shiwei1 (彭诗玮), ZHANG Xi1∗ (张希), ZHU Wangwang1 (朱旺旺), DOU Rui2 (窦瑞) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1063-1070.   DOI: 10.1007/s12204-022-2531-5 Abstract （320）      PDF（pc） （659KB）（36）       Knowledge map    Save At present, most of the studies on autonomous vehicles mainly focus on improving driving safety and efficiency, while less consideration is given to the comfort of passengers. Therefore, in order to gain and optimize quantitative indices for the ride experience of autonomous vehicles, this paper proposes an evaluation method for the correlation between driving behavior and passenger comfort with bidirectional long short-term memory network and attention mechanism. By collecting subjective feeling scores of passengers under different driving styles, and measuring the pressure level with skin conductance response and heart rate variability, the comprehensive quantitative indices of passenger comfort caused by driving behavior are evaluated. Based on this, a personalized comfort evaluation model for passengers with different driving style preferences is established. The results obtained from experiments in open road and closed test areas have validated the effectiveness and feasibility of the method proposed in this paper. Reference | Related Articles | Metrics | Comments（0）

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Attitude Stabilization of Unmanned Underwater Vehicle During Payloads Release DENG Xua (邓旭), FENG Zhengpinga, b∗ (冯正平), HE Chenlua (何晨璐), CUI Zhenhuaa (崔振华) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 766-772.   DOI: 10.1007/s12204-023-2598-7 Abstract （140）      PDF（pc） （765KB）（36）       Knowledge map    Save Large unmanned underwater vehicles can carry big payloads for varied missions and it is desirable for them to possess an upright orientation during payload release. Their attitude can hardly be maintained during and after the phase of payload release. Releasing a payload from the vehicle induces uncertainties not only in rigid-body parameters, e.g, the moment of inertia tensor due to the varying distribution of the masses on board the vehicle, but also in the hydrodynamic derivatives due to the vehicle’s varying geometric profile. A nonlinear attitude stabilizer that is robust to these time-varying model uncertainties is proposed in this paper. Stability is guaranteed via Lyapunov stability theory. The simulation results verify the effectiveness of the proposed approach. Reference | Related Articles | Metrics | Comments（0）

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Wideband Microstrip-to-Microstrip Vialess Vertical Transition Based on Multilayer Liquid Crystal Polymer Technology LIU Weihong , GUAN Dongyang , HUANG Qian , CHEN Liuyang, ZHANG Menglin J Shanghai Jiaotong Univ Sci    2025, 30 (2): 220-226.   DOI: 10.1007/s12204-023-2621-z Abstract （168）      PDF（pc） （1902KB）（34）       Knowledge map    Save A Ka-band wideband microstrip-to-microstrip (MS-to-MS) vialess vertical transition on slotline multimode  resonator (MMR) is presented. The proposed transition mainly consists of a slotline MMR on the common  ground plane, and two microstrip (MS) lines facing each other at the top and third layers in the four-layered liquid  crystal polymer (LCP) substrate. In order to improve the bandwidth of the proposed transition, a U-shaped  branch is added to the top- and third-layer MS lines, separately. The slotline MMR can be properly excited by  setting the position of the U-shaped branch line. As such, a three-pole wideband vertical transition is obtained,  which shows a good transmission performance over a wide frequency range of 29.27—39.95 GHz. The three-pole  wideband vertical transition based on multilayer LCP substrate is designed, fabricated, and measured. Test results  indicate that a wide frequency range of 26.84—36.26 GHz can be obtained with return loss better than −10 dB  and insertion loss less than −3dB. Reference | Related Articles | Metrics | Comments（0）

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Universal Modeling Method of Electrical Impedance Response During Respiration LIU Enkang1 (刘恩康), MA Yixin1, 2∗ (马艺馨), BAI Zixuan1 (白子轩), ZHOU Xing1 (周星), ZHANG Mingzhu1 (张明珠), JIANG Zeyi1 (江泽裔) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 967-978.   DOI: 10.1007/s12204-023-2593-z Abstract （196）      PDF（pc） （1004KB）（34）       Knowledge map    Save In recent years, significant progress has been made through impedance pneumography (IP) in diagnosing pulmonary function. Since there is no need to measure inhalation and exhalation air flow through a pipeline, IP does not increase respiratory resistance and poses no risk of cross-infection, which makes it superior to existing gas flowmeter-based spirometers in clinics. However, the changes in thoracic impedance caused by pulmonary ventilation present significant individual variability. The ratio between pulmonary ventilation volume change (ΔV ) and thoracic impedance change (ΔZ), noted as kΔV/ΔZ , differs among people. IP has to be calibrated for each person by flowmeter-type spirometer before it can be used for quantitative diagnosis. This study aimed to develop a universal model for kΔV/ΔZ using individual parameters such as body height, body mass, body mass index, body fat rate, and chest circumference. The experimental procedure, the way to identify factors for multiple regression via significance analysis and the comparison among different models are presented. This paper demonstrates the possibility of establishing a universal regression model for kΔV/ΔZ , to lay the foundation for the clinical application of IP-based pulmonary function test. Reference | Related Articles | Metrics | Comments（0）

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Random Regret Minimization Model of Carpool Travel Choice for Urban Residents Considering Perceived Heterogeneity and Psychological Distance XIAO Qianga, c∗ (肖强), HE Ruichunb (何瑞春), WANG Ziyia (王子怡) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 995-1008.   DOI: 10.1007/s12204-023-2588-9 Abstract （181）      PDF（pc） （1943KB）（32）       Knowledge map    Save Carpooling is a sustainable, economical, and environmentally friendly solution to reduce air pollution and ease traffic congestion in urban areas. However, existing regret theories lack consideration of the heterogeneity of attribute perception in different ways and the psychological factors that affect regret, so they cannot accurately portray urban residents’ carpool travel decisions and cannot provide a correct explanation of the actual carpool choice behavior. In this paper, based on the analysis of classical random regret minimization models and random regret minimization models considering heterogeneity, the concept of psychological distance is introduced to address shortcomings of the existing models and construct an improved random regret minimization model considering heterogeneity and psychological distance. The results show that the fit and explanatory effect of the improved model proposed in this paper is better than that of the other two models. The psychological distance of travel residents during the Corona Virus Disease 2019 (COVID-19) affects the anticipated regret value and the willingness to carpool. The model can better describe the carpool travel choice mechanism of travelers and effectively explain the carpool travel choice behavior of travelers. Reference | Related Articles | Metrics | Comments（0）

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Multi-GNSS Fusion Real-Time Kinematic Algorithm Based on Extended Kalman Filter Correction Model for Medium-Long Baselines XIA Yang1 (夏杨), REN Guanghui2 (任光辉), WAN Yuan1 (万缘), MAO Xuchu1∗ (茅旭初) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1191-1201.   DOI: 10.1007/s12204-022-2470-1 Abstract （125）      PDF（pc） （1953KB）（31）       Knowledge map    Save In the case of a medium-long baseline, for real-time kinematic (RTK) positioning, the fixed rate of integer ambiguity is low due to the distance between the base station and the observation station. Moreover, the atmospheric delay after differential processing cannot be ignored. For correcting the residual atmospheric errors, we proposed a GPS/BDS/Galileo/GLONASS four-system fusion RTK positioning algorithm, which is based on the extended Kalman filter (EKF) algorithm. After realizing the spatio-temporal unification of multiple global navigation satellite systems (GNSSs), we introduced a parameter estimation of atmospheric errors based on the EKF model, using the least-squares integer ambiguity decorrelation adjustment (LAMBDA) to calculate the integer ambiguity. After conducting experiments for different baselines, the proposed RTK positioning algorithm can achieve centimeter-level positioning accuracy in the case of medium-long baselines. In addition, the time required to solve the fixed solution is shorter than that of the traditional RTK positioning algorithm. Reference | Related Articles | Metrics | Comments（0）

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Visualization System for Closed Thoracic Drainage Puncture Based on Augmented Reality and Ultrafine Diameter Camera Qin Wei, Wang Shuyi, Chen Xueyu, Zhuang Yiwei, Shen Yichun, Shen Yuhán J Shanghai Jiaotong Univ Sci    2025, 30 (3): 417-424.   DOI: 10.1007/s12204-025-2808-6 Abstract （83）      PDF（pc） （1524KB）（27）       Knowledge map    Save Closed thoracic drainage can be performed using a steel-needle-guided chest tube to treat pleural effusion or pneumothorax in clinics. However, the puncture procedure during surgery is invisible, increasing the risk of surgical failure. Therefore, it is necessary to design a visualization system for closed thoracic drainage. Augmented reality (AR) technology can assist in visualizing the internal anatomical structure and determining the insertion point on the body surface. The structure of the currently used steel-needle-guided chest tube was modified by integrating it with an ultrafine diameter camera to provide real-time visualization of the puncture process. After simulation experiments, the overall registration error of the AR method was measured to be within (3.59±0.53) mm, indicating its potential for clinical application. The ultrafine diameter camera module and improved steel-needle-guided chest tube can timely reflect the position of the needle tip in the human body. A comparative experiment showed that video guidance could improve the safety of the puncture process compared to the traditional method. Finally, a qualitative evaluation of the usability of the system was conducted through a questionnaire. This system facilitates the visualization of closed thoracic drainage puncture procedure and provides an implementation scheme to enhance the accuracy and safety of the operative step, which is conducive to reducing the learning curve and improving the proficiency of the doctors. 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 （451）      PDF（pc） （233KB）（25）       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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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 （136）      PDF（pc） （1537KB）（25）       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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Efficient Fully Convolutional Network and Optimization Approach for Robotic Grasping Detection Based on RGB-D Images Nie Wei, Liang Xinwu J Shanghai Jiaotong Univ Sci    2025, 30 (2): 399-416.   DOI: 10.1007/s12204-023-2615-x Abstract （167）      PDF（pc） （6236KB）（25）       Knowledge map    Save Robot grasp detection is a fundamental vision task for robots. Deep learning-based methods have shown excellent results in enhancing the grasp detection capabilities for model-free objects in unstructured scenes. Most popular approaches explore deep network models and exploit RGB-D images combining colour and depth data to acquire enriched feature expressions. However, current work struggles to achieve a satisfactory balance between the accuracy and real-time performance; the variability of RGB and depth feature distributions receives inadequate attention. The treatment of predicted failure cases is also lacking. We propose an efficient fully convolutional network to predict the pixel-level antipodal grasp parameters in RGB-D images. A structure with hierarchical feature fusion is established using multiple lightweight feature extraction blocks. The feature fusion module with 3D global attention is used to select the complementary information in RGB and depth images sufficiently. Additionally, a grasp configuration optimization method based on local grasp path is proposed to cope with the possible failures predicted by the model. Extensive experiments on two public grasping datasets, Cornell and Jacquard, demonstrate that the approach can improve the performance of grasping unknown objects. Reference | Related Articles | Metrics | Comments（0）

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Knowledge-Based Curved Block Construction Scheduling and Application in Shipbuilding JIANG Zuhua1∗(蒋祖华), ZHOU Hongming2(周宏明), TAO Ningrong3(陶宁蓉), LI Baihe1(李柏鹤) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 759-765.   DOI: 10.1007/s12204-022-2544-0 Abstract （192）      PDF（pc） （1037KB）（24）       Knowledge map    Save To increase efficiency in fierce competition, it is necessary and urgent to improve the standard of production planning for shipbuilding. The construction of curved blocks is the bottleneck to improve the efficiency of shipbuilding. Thus it is a key breakthrough for higher shipbuilding productivity to study the curved block production. By analyzing the scheduling problem in curved blocks production, we propose an intelligent curved block production scheduling method and its system based on a knowledge base, and show the main process of the system. The functions of the system include data management, assembly plan generation, plan adjustment, and plan evaluation. In order to deal with the actual situation and inherit the empirical knowledge, the system extracts some rules to control block selecting, algorithm selection, and evaluation thresholds to build a production decision-making knowledge base in the curved block scheduling system. The proposed knowledge base could be referred and modified by users, especially after a few interactions between the users and the knowledge base. The final assembly plan can be visualized and evaluated to facilitate the observation of plan implementation and effects of the decisions in the process. Finally, the system is verified by a large shipyard in Shanghai using real data and the results illustrate that the proposed method can perform the knowledge-based scheduling for curved blocks construction effectively. 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 （139）      PDF（pc） （1270KB）（24）       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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Neural Network Optimization of Multivariate KDE Bandwidth for Buoy Spatial Information XU Liangkun1, 2 (徐良坤), XUE Han2∗ (薛晗), JIN Yongxing1 (金永兴), ZHOU Shibo2 (周世波) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 773-779.   DOI: 10.1007/s12204-022-2466-x Abstract （191）      PDF（pc） （731KB）（23）       Knowledge map    Save It is one of the responsibilities of the navigation support department to ensure the correct layout position of the light buoy and provide as accurate position information as possible for ship navigation and positioning. If the position deviation of the light buoy is too large to be detected in time, sending wrong navigation assistance information to the ship will directly affect the navigation safety of the ship and increase the pressure on the management department. Therefore, mastering the offset characteristics of light buoy is of great significance for the maintenance of light buoy and improving the navigation aid efficiency of light buoy. Kernel density estimation can intuitively express the spatial and temporal distribution characteristics of buoy position, and indicates the intensive areas of buoy position in the channel. In this paper, in order to speed up deciding the optimal variable width of kernel density estimator, an improved adaptive variable width kernel density estimator is proposed, which reduces the risk of too smooth probability density estimation phenomenon and improves the estimation accuracy of probability density. A fractional recurrent neural network is designed to search the optimal bandwidth of kernel density estimator. It not only achieves faster training speed, but also improves the estimation accuracy of probability density. Reference | Related Articles | Metrics | Comments（0）

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Optimization of Highway-Railway Level Crossing in Port Area with Priority of Key Lanes ZHANG He(张赫), ZHOU Zhengkai(周正凯), LIN Huanyu（林环宇）, WANG Tianci（王天慈） J Shanghai Jiaotong Univ Sci    2024, 29 (5): 791-800.   DOI: 10.1007/s12204-022-2553-z Abstract （196）      PDF（pc） （689KB）（22）       Knowledge map    Save When controlling the signal of highway-rail level crossings in the port area, the multi-objective signal optimization model is not applicable due to the cross effect of roads and railways and the priority of incoming vehicles. Therefore, in order to ensure that the inbound truck fleet enters the port directly without being affected by the train when passing through the highway-rail level crossing in the port area, the queuing of vehicles in front of the port needs to be reduced, and the priority should be given to the inbound trucks. Based on the idea of priority on key lanes, this study relies on speed guidance information to guide the fleet to shift reasonably, postpone or early arrive at the railway gate. At the same time, the optimization goal is to minimize the delays at intersections, the number of stops, and the vehicle exhaust emissions. The measured data of road-rail level crossings in Dayaowan Port Area of Dalian were selected, and it was re-developed under the VISSIM environment by serial interface to realize signal optimization control under vehicle speed guidance. The original timing plan, multi-objective timing optimization plan and key lanes priority are given to the optimization scheme for simulation experiments. The results show that the multi-objective optimization scheme and the optimization scheme under the priority of key lanes can generally improve the traffic capacity of road-rail level crossings. Compared with the original plan, the optimization plan under the priority of key lanes reduces the delay by 33.3%, the number of stops is reduced by 25%, and the vehicle exhaust emissions are reduced by 31.3%. It proves the effectiveness of the optimization scheme for highway-rail level crossings in the port area under the priority of key lanes, and it is more suitable for highway-rail level crossings. Reference | Related Articles | Metrics | Comments（0）

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Coordination Design of a Power-Assisted Ankle Exoskeleton Robot Based on Active-Passive Combined Drive HE Guisong (贺贵松), HUANG Xuegong* (黄学功),LI Feng（李峰) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 197-208.   DOI: 10.1007/s12204-023-2589-8 Abstract （320）      PDF（pc） （2027KB）（21）       Knowledge map    Save With the continuous escalation of modern war, soldiers need to transport more combat materials to the combat area. The limited load-bearing capacity of soldiers seriously restricts their carrying capacity and mobility. It is urgent to develop a power-assisted exoskeleton robot suitable for individual combat. In the past, most power-assisted exoskeleton robots were driven by motors. This driving method has an excellent powerassisted effect, but the endurance is often insufficient. In view of this shortcoming, this study designed an ankle exoskeleton robot based on an active-passive combined drive through simulation analysis of human motion. It used OpenSim software to simulate and verify that the addition of spring could achieve a good effect. At the same time, according to the gait characteristics of the human body, the gait planning of an exoskeleton robot was carried out. Afterwards, theoretical analysis explained that the cooperation among spring, motor and wearer could be realized in this gait. Finally, the assisting ability and driving coordination of the active-passive combination driven ankle exoskeleton robot were verified through experiments. 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 （136）      PDF（pc） （3708KB）（20）       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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Novel Compact Dual-Band Bandpass Filter Based on Multilayer Liquid Crystal Polymer Substrate Liu Weihong, Liu Qingran J Shanghai Jiaotong Univ Sci    2025, 30 (2): 233-238.   DOI: 10.1007/s12204-023-2659-y Abstract （143）      PDF（pc） （1863KB）（20）       Knowledge map    Save In this paper, a compact defected ground structure loaded ultra high frequency dual-band bandpass filter is designed and implemented based on multilayer liquid crystal polymer technology. This novel filter is simply composed with several lumped and semi-lumped elements, to create a dual-passband response. In order to enhance the out-of-band rejection, a feedback capacitor Cz at the in/out ports of the filter is introduced, and four transmission zeros (TZs) are obtained outside the pass band. Furthermore, the position of TZs can be determined by adjusting the value of Cz. The schematic and design process of the filter are given in this paper. The center frequencies of dual-band bandpass filter are 0.9GHz and 2.45GHz, and the 3-dB bandwidths are 13.7% and 14.3%, respectively. The circuit size is 11mm × 9.5mm × 0.193mm. The proposed filter has been fabricated and tested, and the measured result is in good agreement with the simulation result. Reference | Related Articles | Metrics | Comments（0）

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Model Predictive Control Method Based on Data-Driven Approach for Permanent Magnet Synchronous Motor Control System Li Songyang, Chen Wenbo, Wan Heng J Shanghai Jiaotong Univ Sci    2025, 30 (2): 270-279.   DOI: 10.1007/s12204-023-2600-4 Abstract （130）      PDF（pc） （842KB）（20）       Knowledge map    Save Permanent magnet synchronous motor (PMSM) is widely used in alternating current servo systems as it provides high efficiency, high power density, and a wide speed regulation range. The servo system is placing higher demands on its control performance. The model predictive control (MPC) algorithm is emerging as a potential high-performance motor control algorithm due to its capability of handling multiple-input and multipleoutput variables and imposed constraints. For the MPC used in the PMSM control process, there is a nonlinear disturbance caused by the change of electromagnetic parameters or load disturbance that may lead to a mismatch between the nominal model and the controlled object, which causes the prediction error and thus affects the dynamic stability of the control system. This paper proposes a data-driven MPC strategy in which the historical data in an appropriate range are utilized to eliminate the impact of parameter mismatch and further improve the control performance. The stability of the proposed algorithm is proved as the simulation demonstrates the feasibility. Compared with the classical MPC strategy, the superiority of the algorithm has also been verified. Reference | Related Articles | Metrics | Comments（0）

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Dynamic Train Vertical Sperling Index Evaluation Model Considering Wheel-Rail Contact Loss LIU Yiling1 (刘怡伶), ZHANG Jingwei1 (张经纬), LIU Xuewen1∗ (刘学文), WANG Yansong1 (王岩松), ZHOU Yueting2 (周跃亭) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1103-1115.   DOI: 10.1007/s12204-022-2551-1 Abstract （112）      PDF（pc） （1175KB）（20）       Knowledge map    Save In this study, a half-space 13-degree-of-freedom vehicle model, a double track model, and a train-bridge interaction model were integrated to form a combined people-train-rail-bridge interaction model to analyze the vertical Sperling index of the train body and passengers as realistically as possible. In this bigger, more complete, and novel model, the separation between the vehicle and bridge is considered. By comparing measured data and simulated results obtained using the proposed model with the Newmark-Beta algorithm, the effectiveness of the model was verified, and the results demonstrated that these two values were very close. Upon further numerical analysis, the dynamic responses of the train and the three equivalent human bodies at different train speeds were computed using the developed vehicle-structure dynamic analysis program with different abruptness values in the random rail irregularities. The results of these four dynamic responses revealed that the rail irregularities affected the vertical acceleration of the three equivalent human bodies and train, and the best Sperling index evaluation standard for the train was not fixed (as assumed when only considering the train body) but varied with the passenger position as the train traveled over irregularities. Reference | Related Articles | Metrics | Comments（0）

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Online Vehicle Forensics Method of Responsible Party for Accidents Based on LSTM-BiDBN External Intrusion Detection LIU Wen1, 3 (刘文), XU Jianxin2, 4 (许剑新), YANG Genke1, 3∗ (杨根科), CHEN Yuanfang5 (陈媛芳) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1161-1168.   DOI: 10.1007/s12204-022-2549-8 Abstract （237）      PDF（pc） （1001KB）（20）       Knowledge map    Save Vehicle data is one of the important sources of traffic accident digital forensics. We propose a novel method using long short-term memory-deep belief network by binary encoding (LSTM-BiDBN) controller area network identifier (CAN ID) to extract the event sequence of CAN IDs and the semantic of CAN IDs themselves. Instead of detecting attacks only aimed at a specific CAN ID, the proposed method fully considers the potential interaction between electronic control units. By this means, we can detect whether the vehicle has been invaded by the outside, to online determine the responsible party of the accident. We use our LSTM-BiDBN to distinguish attack-free and abnormal situations on CAN-intrusion-dataset. Experimental results show that our proposed method is more effective in identifying anomalies caused by denial of service attack, fuzzy attack and impersonation attack with an accuracy value of 97.02%, a false-positive rate of 6.09%, and a false-negative rate of 1.94% compared with traditional methods. Reference | Related Articles | Metrics | Comments（0）

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Mechanical and Permeability Properties of Radial-Gradient Bone Scaffolds Developed by Voronoi Tessellation for Bone Tissue Engineering Xu Qingyu, Hai Jizhe, Shan Chunlong, Li Haijie J Shanghai Jiaotong Univ Sci    2025, 30 (3): 433-445.   DOI: 10.1007/s12204-024-2770-8 Abstract （69）      PDF（pc） （4136KB）（19）       Knowledge map    Save Irregular bone scaffolds fabricated using the Voronoi tessellation method resemble the morphology and properties of human cancellous bones. This has become a prominent topic in bone tissue engineering research in recent years. However, studies on the radial-gradient design of irregular bionic scaffolds are limited. Therefore, this study aims to develop a radial-gradient structure similar to that of natural long bones, enhancing the development of bionic bone scaffolds. A novel gradient method was adopted to maintain constant porosity, control the seed sitespecific distribution within the irregular porous structure, and vary the strut diameter to generate radial gradients. The irregular scaffolds were compared with four conventional scaffolds (cube, pillar BCC, vintiles, and diamond) in terms of permeability, stress concentration characteristics, and mechanical properties. The results indicate that the radial-gradient irregular porous structure boasts the widest permeability range and superior stress distribution compared to conventional scaffolds. With an elastic modulus ranging from 4.20 GPa to 22.96 GPa and a yield strength between 68.37 MPa and 149.40 MPa, it meets bone implant performance requirements and demonstrates significant application potential. Reference | Related Articles | Metrics | Comments（0）

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Adjacent Segment Biomechanical Changes After Implantation of Cage Plus Plate or Zero-Profile Device in Different Segmental Anterior Cervical Discectomy and Fusion YE Peng (叶鹏), FU Rongchang∗ (富荣昌), WANG Zhaoyao (王召耀) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 166-174.   DOI: 10.1007/s12204-023-2633-8 Abstract （377）      PDF（pc） （930KB）（19）       Knowledge map    Save Cage plus plate (CP) and zero-profile (Zero-P) devices are widely used in anterior cervical discectomy and fusion (ACDF). This study aimed to compare adjacent segment biomechanical changes after ACDF when using Zero-P device and CP in different segments. First, complete C1—C7 cervical segments were constructed and validated. Meanwhile, four surgery models were developed by implanting the Zero-P device or CP into C4—C5 or C5—C6 segments based on the intact model. The segmental range of motion (ROM) and maximum value of the intradiscal pressure of the surgery models were compared with those of the intact model. The implantation of CP and Zero-P devices in C4—C5 segments decreased ROM by about 91.6% and 84.3%, respectively, and increased adjacent segment ROM by about 8.3% and 6.82%, respectively. The implantation of CP and Zero-P devices in C5—C6 segments decreased ROM by about 93.3% and 89.9%, respectively, while increasing adjacent segment ROM by about 4.9% and 4%, respectively. Furthermore, the implantation of CP and Zero-P devices increased the intradiscal pressure in the adjacent segments of C4—C5 segments by about 4.5% and 6.7%, respectively. The implantation of CP and Zero-P devices significantly increased the intradiscal pressure in the adjacent segments of C5—C6 by about 54.1% and 15.4%, respectively. In conclusion, CP and Zero-P fusion systems can significantly reduce the ROM of the fusion implant segment in ACDF while increasing the ROM and intradiscal pressure of adjacent segments. Results showed that Zero-P fusion system is the best choice for C5—C6 segmental ACDF. However, further studies are needed to select the most suitable cervical fusion system for C4—C5 segmental ACDF. Therefore, this study provides biomechanical recommendations for clinical surgery. Reference | Related Articles | Metrics | Comments（0）

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Natural Vibration Characteristics for Prestressed Concrete-Filled Rectangular Steel Tube Simply Supported Beam YE Junxian (叶俊贤), HUANG Weixuan (黄维璇), LI Siping (李四平) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 940-944.   DOI: 10.1007/s12204-023-2617-8 Abstract （151）      PDF（pc） （835KB）（18）       Knowledge map    Save The dynamic control equation of a new prestressed partially concrete-filled rectangular steel tube (CFRT) beam can be derived based on D’Alembert’s principle. It is used to infer the theoretical results of the dynamic characteristics for the prestressed CFRT beam. Additionally, the finite element model is set up by ABAQUS for simulation analysis. The results show that the natural vibration frequencies and mode function of the prestressed CFRT simply supported beam calculated by the theoretical formulas are reliable since the relative errors of the first-order frequencies under different prestressing levels are within 6% compared with the finite element results. Further analysis of the prestressing parameters is carried out using the theoretical formulas, in which factors such as the prestressing level, eccentricity of tendons, and tensile stiffness of prestressed tendons have different influences on the natural vibration frequencies. Finally, it provides a theoretical basis for the dynamic design of the prestressed CFRT beams. Reference | Related Articles | Metrics | Comments（0）

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Traffic Police Punishment Mechanism Promotes Cooperation in Snowdrift Game on Lattice ZU Jinjing (祖金菁), XIANG Wei∗ (向伟), KANG Qin (康钦), YANG Hang (杨航), WANG Hancheng (王瀚程) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1116-1125.   DOI: 10.1007/s12204-022-2533-3 Abstract （123）      PDF（pc） （2674KB）（18）       Knowledge map    Save Traffic issues have always received enthusiastic attention from the society. To better simulate the traffic environment, we use the well-known snowdrift game (SDG). Punishment has been regarded as a significant method to promote cooperation. We propose a novel punishment mechanism and discuss its influence on the cooperation of the SDG. Considering that the snowball causes traffic jam, we add the role of the traffic police in the SDG. When the traffic police choose to cooperate, they have the right to punish the defectors. The scope of jurisdiction, the record of punishment and the method of deployment are decisive factors in deciding whether or not to punish the defectors and the severity of the punishment. Whether to sanction the defector and the severity of the punishment is jointly determined by the traffic police’s punishment record, jurisdiction, and deployment method. Through extensive simulation, we found that the difference between the two distribution methods becomes smaller as the jurisdiction becomes smaller. We need to choose the dominant distribution method based on the jurisdiction and the neighbor pattern. The results demonstrate that the punitive record, jurisdiction and distribution method all have an important impact on the SDG and traffic governance. Reference | Related Articles | Metrics | Comments（0）

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Named Entity Recognition of Design Specification Integrated with High-Quality Topic and Attention Mechanism ZHOU Cheng (周成), JIANG Zuhua∗ (蒋祖华) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1169-1180.   DOI: 10.1007/s12204-022-2534-2 Abstract （155）      PDF（pc） （1857KB）（17）       Knowledge map    Save Automatic extraction of key data from design specifications is an important means to assist in engineering design automation. Considering the characteristics of diverse data types, small scale, insufficient character information content and strong contextual relevance of design specification, a named entity recognition model integrated with high-quality topic and attention mechanism, namely Quality Topic-Char Embedding-BiLSTMAttention-CRF, was proposed to automatically identify entities in design specification. Based on the topic model,an improved algorithm for high-quality topic extraction was proposed first, and then the high-quality topic information obtained was added into the distributed representation of Chinese characters to better enrich character features. Next, the attention mechanism was used in parallel on the basis of the BiLSTM-CRF model to fully mine the contextual semantic information. Finally, the experiment was performed on the collected corpus of Chinese ship design specification, and the model was compared with multiple sets of models. The results show that F-score (harmonic mean of precision and recall) of the model is 80.24%. The model performs better than other models in design specification, and is expected to provide an automatic means for engineering design. Reference | Related Articles | Metrics | Comments（0）

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Longitudinal Motion Simulation of Stratospheric Airship Under Dynamic Response of Moving-Mass Actuator XU Minjie1, 2 (徐敏杰), WANG Quanbao1∗ (王全保), DUAN Dengping1 (段登平) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 1139-1150.   DOI: 10.1007/s12204-022-2552-0 Abstract （147）      PDF（pc） （1574KB）（17）       Knowledge map    Save In this paper, a design method of moving-mass stratospheric airship with constant total mass is presented, and the general dynamics equation based on Newton-Euler method is derived. Considering the timedelay of the slider command response and the dynamic coupling to the airship’s state parameters, a position tracking controller with input and state constraints was designed to make the dynamic response system of the slider have critical damping characteristics. By taking the longitudinal attitude motion of moving-mass stratospheric airship as the research object, parametric modeling and attitude control simulation were carried out, and the attitude control ability of moving-mass control under different mass ratios was analyzed. The simulation results show that the attitude control ability is not affected by airspeed, and the mass ratio of slider is the main factor affecting the attitude control ability. The parameters of the slider controller have a direct influence on the dynamic performance of attitude control and also determine the dynamic coupling level of the airship. Compared with the attitude control based on the aerodynamic control surface, moving-mass control can make the airspeed and attack angle converged to the initial state at the steady state, and keep a good aerodynamic shape. Reference | Related Articles | Metrics | Comments（0）

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Direct Ink Writing Method of Fractal Wearable Flexible Sensor Based on Conductive Graphene/Polydimethylsiloxane Ink CHEN Junling1, 2, 3 (陈俊伶), GAO Feiyang1, 3 (高飞扬), ZHANG Liming1, 3 (张黎明), ZHENG Xiongfei1, 3(郑雄飞) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 18-26.   DOI: 10.1007/s12204-023-2687-7 Abstract （358）      PDF（pc） （1712KB）（17）       Knowledge map    Save Flexible electronic technology has laid the foundation for complex human-computer interaction system, and has attracted great attention in the field of human motion detection and soft robotics. Graphene has received an extensive attention due to its excellent electrical conductivity; however, how to use it to fabricate wearable flexible sensors with complex structures remains challenging. In this study, we studied the rheological behavior of graphene/polydimethylsiloxane ink and proposed an optimal graphene ratio, which makes the ink have a good printability and conductivity at the same time. Then, based on the theory of Peano fractal layout, we proposed a two-dimensional structure that can withstand multi-directional tension by replacing the traditional arris structure with the arc structure. After that, we manufactured circular arc fractal structure sensor by adjusting ink composition and printing structure through direct ink writing method. Finally, we evaluated the detection performance and repeatability of the sensor. This method provides a simple and effective solution for fabricating wearable flexible sensors and exhibits the potential to fabricate 3D complex flexible electronic devices. Reference | Related Articles | Metrics | Comments（0）

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Augmented Reality Based Navigation System for Endoscopic Transnasal Optic Canal Decompression FU Hang1 (傅航),XU Jiangchang1 (许江长), LI Yinwei2，4* (李寅炜),ZHOU Huifang2，4 (周慧芳),CHEN Xiaojun1，3* (陈晓军) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 34-42.   DOI: 10.1007/s12204-024-2722-3 Abstract （280）      PDF（pc） （2194KB）（17）       Knowledge map    Save Endoscopic transnasal optic nerve decompression surgery plays a crucial role in minimal invasive treatment of complex traumatic optic neuropathy. However, a major challenge faced during the procedure is the inability to visualize the optic nerve intraoperatively. To address this issue, an endoscopic image-based augmented reality surgical navigation system is developed in this study. The system aims to virtually fuse the optic nerve onto the endoscopic images, assisting surgeons in determining the optic nerve’s position and reducing surgical risks. First, a calibration algorithm based on a checkerboard grid of immobile points is proposed, building upon existing calibration methods. Additionally, to tackle accuracy issues associated with augmented reality technology, an optical navigation and visual fusion compensation algorithm is proposed to improve the intraoperative tracking accuracy. To evaluate the system’s performance, model experiments were meticulously designed and conducted. The results confirm the accuracy and stability of the proposed system, with an average tracking error of (0.99 ± 0.46) mm. This outcome demonstrates the effectiveness of the proposed algorithm in improving the augmented reality surgical navigation system’s accuracy. Furthermore, the system successfully displays hidden optic nerves and other deep tissues, thus showcasing the promising potential for future applications in orbital and maxillofacial surgery. Reference | Related Articles | Metrics | Comments（0）

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Predictive Simulation of External Truck Operation Time in a Container Terminal Based on Traffic Big Data DU Ye1 (杜晔), ZHAO Yifei2 (赵一飞), GAO Deyi1 (高德毅) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 801-808.   DOI: 10.1007/s12204-022-2415-8 Abstract （261）      PDF（pc） （620KB）（17）       Knowledge map    Save The operation time of external trucks in a container terminal is one of port operation key performance indicators concerned by port operators, external truck operators and related government authorities. With the traffic big data combined with the operation characteristics of the container terminal, the system dynamics method is used to build the simulation model of the operation system for external trucks. The simulation results of the operation time of external trucks are consistent with the actual situation, which provides an effective way to eliminate the “black box” of the operation time of the external trucks. The model can also be applied in multiple scenarios by using the traffic big data, and the simulation results can be adopted by the relevant organizations. Reference | Related Articles | Metrics | Comments（0）

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Weld Defect Monitoring Based on Two-Stage Convolutional Neural Network Xiao Wenbo, Xiong Jiakai, Yu Lesheng, He Yinshui, Ma Guohong J Shanghai Jiaotong Univ Sci    2025, 30 (2): 291-299.   DOI: 10.1007/s12204-023-2608-9 Abstract （153）      PDF（pc） （1287KB）（17）       Knowledge map    Save Zn vapour is easily generated on the surface by fusion welding galvanized steel sheet, resulting in the formation of defects. Rapidly developing computer vision sensing technology collects weld images in the welding process, then obtains laser fringe information through digital image processing, identifies welding defects, and finally realizes online control of weld defects. The performance of a convolutional neural network is related to its structure and the quality of the input image. The acquired original images are labeled with LabelMe, and repeated attempts are made to determine the appropriate filtering and edge detection image preprocessing methods. Two-stage convolutional neural networks with different structures are built on the Tensorflow deep learning framework, different thresholds of intersection over union are set, and deep learning methods are used to evaluate the collected original images and the preprocessed images separately. Compared with the test results, the comprehensive performance of the improved feature pyramid networks algorithm based on the basic network VGG16 is lower than that of the basic network Resnet101. Edge detection of the image will significantly improve the accuracy of the model. Adding blur will reduce the accuracy of the model slightly; however, the overall performance of the improved algorithm is still relatively good, which proves the stability of the algorithm. The self-developed software inspection system can be used for image preprocessing and defect recognition, which can be used to record the number and location of typical defects in continuous welds. Reference | Related Articles | Metrics | Comments（0）