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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 （1533）      PDF（pc） （1179KB）（2040）       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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Applications of Polypeptide Hydrogels in Cartilage-Regeneration Engineering HU Yinghan1 (胡颖涵)，ZHU Zegu1 (朱泽宇)， TENG Lin2 (滕林)， HE Yushi3 (何雨石)，ZOU Derong1 (邹德荣)，LU Jiayu1*(陆家瑜) J Shanghai Jiaotong Univ Sci    2023, 28 (4): 468-.   DOI: 10.1007/s12204-022-2507-5 Abstract （449）      PDF（pc） （3066KB）（1702）       Knowledge map    Save Articular cartilage defects are considered to be associated with the development of osteoarthritis. Research on relevant tissue regeneration is important in the treatment of osteoarthritis. The scaffolds applied incartilage regeneration should have good histocompatibility and mechanical properties, as well as no cytotoxicity,and promote the proliferation and differentiation of seed cells. Different combinations of peptide sequences inpolypeptide hydrogels endow them with unique characteristics including excellent biodegradability and accuratesimulation of the extracellular matrix of chondrocytes to maintain the stability of the chondrogenic phenotypeand facilitate articular hyaline cartilage regeneration. Thus, the application of polypeptide hydrogels for cartilage regeneration has a bright future. In this study, the research progress of polypeptide hydrogels used incartilage-regeneration engineering is systematically reviewed. The characteristics, limitations, and prospects ofthese materials are evaluated. 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 （544）      PDF（pc） （1829KB）（1623）       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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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 （616）      PDF（pc） （1518KB）（1457）       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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Fault Diagnosis for Rolling Element Bearing in Dataset Bias Scenario HOU Liangsheng(侯良生),ZHANG Jundong*(张均东) J Shanghai Jiaotong Univ Sci    2023, 28 (5): 638-651.   DOI: 10.1007/s12204-021-2320-6 Abstract （293）      PDF（pc） （1575KB）（1455）       Knowledge map    Save Recently, data-driven methods, especially deep learning, outperform other methods for rolling element bearing (REB) fault diagnosis. Nevertheless, most research work assumes that REB dataset is unbiased. In the real industry applications, the dataset bias exists with REB owing to varying REB working conditions and noise interference. Recently proposed adversarial discriminative domain adaptation (ADDA) is an increasingly popular incarnation to solve dataset bias problem. However, it mainly devotes to realizing domain alignments, and ignores class-level alignments; it can cause degradation of classification performance. In this study, we propose a new REB fault diagnosis model based on improved ADDA to address dataset bias. The proposed diagnosis model realizes domain- and class-level alignments in dataset bias scenario; it consists of two feature extractors, a domain discriminator, and two label classifiers. The feature extractors and domain discriminator are trained in an adversarial manner to minimize the domain difference in feature extractors. The domain discrepancy in label classifier is reduced by minimizing correlation alignment (CORAL) loss. We evaluate the proposed model on the Case Western Reserve University (CWRU) bearing dataset and Paderborn University bearing dataset. The proposed method yields better results than other methods and has good prospects for industrial applications. 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 （616）      PDF（pc） （4397KB）（867）       Knowledge map    Save Frosting is an inevitable adverse phenomenon in many fields such as industrial refrigeration, cryogenics, and heat pump air conditioning, which may influence the efficiency of the equipment and increase the energy consumption of the system. The complicated louvered-fin structure and fluid-channels arrangements of the microchannel heat exchanger (HEX) will affect the heat transfer performance and frosting characteristics. First, this article analyzes different factors such as refrigerant distribution, refrigerant flow pattern, and HEX surface temperature distribution. Further, combined with the features of the microchannel HEX, the existing anti-frosting technologies and various methods of surface treatment for anti-frosting are summarized. The review focuses on the preparation of superhydrophobic surfaces and their superior properties. Furthermore, the internal mechanism is analyzed in conjunction with the relevant research of our group. Superhydrophobic character has excellent anti-frosting performance and heat transfer performance, which is of great significance for improving energy-saving and system performance. Finally, the future development of superhydrophobic surface technology is analyzed and prospected. Reference | Related Articles | Metrics | Comments（0）

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A Novel Cable-Driven Soft Robot for Surgery LI Ru1 (李茹), CHEN Fang2 (陈方), YU Wenwei3 (俞文伟), IGARASH Tatsuo3,4, SHU Xiongpeng1 (舒雄鹏), XIE Le1,5,6∗ (谢叻) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 60-72.   DOI: 10.1007/s12204-022-2497-3 Abstract （525）      PDF（pc） （2939KB）（761）       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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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 （1556）      PDF（pc） （1195KB）（639）       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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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 （525）      PDF（pc） （1734KB）（635）       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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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 （242）      PDF（pc） （914KB）（582）       Knowledge map    Save Technical advances and sustainable development tendency accelerate the implementation of electric trucks. However, the penetration of dynamic charging tariff policy poses a huge challenge to the cost-optimal operation of the electric truck fleet. To this end, a two-stage stochastic electric vehicle routing model is formulated to support cost-efficient routing and charging decisions. Furthermore, an experimental study based on a real-world distribution network is conducted to evaluate impacts of dynamic charging tariffs on logistics planning. The results show that the daily operation cost can reduce by 3.57% to 5.55% as the number of dynamic charging stations increases. The value of stochastic solution confirms the benefits of implementing stochastic programming model,which will ensure a lower operation cost in the long-term through robust route planning. Reference | Related Articles | Metrics | Comments（0）

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Multi-Agent Path Planning Method Based on Improved Deep Q-Network in Dynamic Environments LI Shuyi (李舒逸), LI Minzhe (李旻哲), JING Zhongliang∗ (敬忠良) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 601-612.   DOI: 10.1007/s12204-024-2732-1 Abstract （1289）      PDF（pc） （1213KB）（575）       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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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 （613）      PDF（pc） （1462KB）（514）       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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Medical Image Encryption Based on Josephus Traversing and Hyperchaotic Lorenz System YANG Na (杨娜), ZHANG Shuxia (张淑霞), BAI Mudan (白牡丹), LI Shanshan∗ (李珊珊) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 91-108.   DOI: 10.1007/s12204-022-2555-x Abstract （409）      PDF（pc） （8082KB）（439）       Knowledge map    Save This study proposes a new medical image encryption scheme based on Josephus traversing and hyperchaotic Lorenz system. First, a chaotic sequence is generated through hyperchaotic system. This hyperchaotic sequence is used in the scrambling and diffusion stages of the algorithm. Second, in the scrambling process, the image is initially confused by Josephus scrambling, and then the image is further confused by Arnold map. Finally, generated hyperchaos sequence and exclusive OR operation is used for the image to carry on the positive and reverse diffusion to change the pixel value of the image and further hide the effective information of the image. In addition, the information of the plaintext image is used to generate keys used in the algorithm, which increases the ability of resisting plaintext attack. Experimental results and security analysis show that the scheme can effectively hide plaintext image information according to the characteristics of medical images, and is resistant to common types of attacks. In addition, this scheme performs well in the experiments of robustness, which shows that the scheme can solve the problem of image damage in telemedicine. It has a positive significance for the future research. Reference | Related Articles | Metrics | Comments（0）

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Multi-Robot Task Allocation Using Multimodal Multi-Objective Evolutionary Algorithm Based on Deep Reinforcement Learning MIAO Zhenhua(苗镇华), HUANG Wentao(黄文焘), ZHANG Yilian(张依恋), FAN Qinqin(范勤勤) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 377-387.   DOI: 10.1007/s12204-023-2679-7 Abstract （1246）      PDF（pc） （975KB）（426）       Knowledge map    Save The overall performance of multi-robot collaborative systems is significantly affected by the multirobot task allocation. To improve the effectiveness, robustness, and safety of multi-robot collaborative systems,a multimodal multi-objective evolutionary algorithm based on deep reinforcement learning is proposed in this paper. The improved multimodal multi-objective evolutionary algorithm is used to solve multi-robot task allocation problems. Moreover, a deep reinforcement learning strategy is used in the last generation to provide a high-quality path for each assigned robot via an end-to-end manner. Comparisons with three popular multimodal multi-objective evolutionary algorithms on three different scenarios of multi-robot task allocation problems are carried out to verify the performance of the proposed algorithm. The experimental test results show that the proposed algorithm can generate sufficient equivalent schemes to improve the availability and robustness of multirobot collaborative systems in uncertain environments, and also produce the best scheme to improve the overall task execution efficiency of multi-robot collaborative systems. Reference | Related Articles | Metrics | Comments（0）

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Toughening Mechanism of Large Heat Input Weld Metal for Marine Engineering Extra-Thick Plate LENG Junjie1 (冷俊杰), DI Xinjie,2*1 (邸新杰), LI Chengning1,2 (利成宁), CHENG Shanghua3 (程尚华) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 349-360.   DOI: 10.1007/s12204-023-2638-3 Abstract （404）      PDF（pc） （4684KB）（361）       Knowledge map    Save In order to study the latest designed large heat input welding material of marine engineering extrathick plate, EH36 steel was joined by using twin-wire submerged arc welding with heat inputs of 85, 100 and 115 kJ/cm separately. Meanwhile, the microstructure and mechanical properties were evaluated to explore the toughening mechanism of weld metal. Results show that a lot of active inclusions are obtained in the weld metal due to the design idea of low carbon and oxide metallurgy, which contributes to the generation of numerous fine and interlocking acicular ferrite. The acicular ferrite volume ratio of weld metal exceeds 60%. Moreover, the impact energy at −40 ◦C surpasses 115 J and the crack tip opening displacement value at −10 ◦C is more than 0.2 mm under three heat inputs owing to the role of acicular ferrite, of which 85 kJ/cm is the best. The martensiteaustenite constituents are minor in size and the microstructure of the weld metal in reheated zone is dominated by small massive equiaxed ferrite, without impairing the toughness. As the heat input increases, the content of acicular ferrite drops and then rises; the impact toughness and fracture toughness first worsen consequently and then stabilize on account of the dramatic expansion of the proeutectoid ferrite size. Reference | Related Articles | Metrics | Comments（0）

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Distributed Cooperative Anti-Disturbance Control for High-Order MIMO Nonlinear Multi-Agent Systems JIN Feiyu (金飞宇), CHEN Longsheng∗ (陈龙胜), LI Tongshuai (李统帅), SHI Tongxin (石童昕) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 656-666.   DOI: 10.1007/s12204-023-2673-0 Abstract （283）      PDF（pc） （680KB）（346）       Knowledge map    Save To solve the synchronization and tracking problems, a cooperative control scheme is proposed for a class of higher-order multi-input and multi-output (MIMO) nonlinear multi-agent systems (MASs) subjected to uncertainties and external disturbances. First, coupled relationships among Laplace matrix, leader-following adjacency matrix and consensus error are analyzed based on undirected graph. Furthermore, nonlinear disturbance observers (NDOs) are designed to estimate compounded disturbances in MASs, and a distributed cooperative antidisturbance control protocol is proposed for high-order MIMO nonlinear MASs based on the outputs of NDOs and dynamic surface control approach. Finally, the feasibility and effectiveness of the proposed scheme are proven based on Lyapunov stability theory and simulation experiments. Reference | Related Articles | Metrics | Comments（0）

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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 （1177）      PDF（pc） （1017KB）（334）       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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Numerical Simulation of Radial Ultrasonic Assisted MIG Welding Arc HONG Lei1 (洪蕾), XIAO Hao1 (肖皓), YE Jia2 (叶佳), MA Guohong1* (马国红) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 330-338.   DOI: 10.1007/s12204-021-2380-7 Abstract （406）      PDF（pc） （1906KB）（328）       Knowledge map    Save The numerical simulation of arc was carried out for both conventional melt inert gas (MIG) welding and ultrasonic assisted melt inert gas (U-MIG) welding. Based on the model established by Fluent, the arc shape, temperature field, and potential distribution were simulated. The study found that the shape of the arc changed when ultrasonic was added radially; the high-temperature area of the arc stretched, and the temperature peak increased. But as the current increased, the increase in temperature decreased. In addition, under the same conditions, the potential of U-MIG decreased and the pressure on the workpiece increased. To verify the accuracy of the simulation results, welding experiments under identical conditions were carried out, and a high-speed camera was used to collect dynamic pictures of the arc. The simulation results were in a favorable agreement with the experimental results, which provided a certain reference value for ultrasonic assisted arc welding. Reference | Related Articles | Metrics | Comments（0）

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Analysis of Software Trustworthiness Based on FAHP-CRITIC Method GAO Xiaotong11 (高晓彤), MA Yanfang1，2* (马艳芳), ZHOU Wei1 周伟) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 588-600.   DOI: 10.1007/s12204-022-2496-4 Abstract （292）      PDF（pc） （740KB）（328）       Knowledge map    Save Software trustworthiness includes many attributes. Reasonable weight allocation of trustworthy attributes plays a key role in the software trustworthiness measurement. In practical application, attribute weight usually comes from experts’ evaluation to attributes and hidden information derived from attributes. Therefore, when the weight of attributes is researched, it is necessary to consider weight from subjective and objective aspects. First, a novel weight allocation method is proposed by combining the fuzzy analytical hierarchy process (FAHP) method and the criteria importance though intercrieria correlation (CRITIC) method. Second, based on the weight allocation method, the trustworthiness measurement models of component-based software are established according to the seven combination structures of components. Third, the model reasonability is verified via proving some metric criteria. Finally, a case is carried out. According to the comparison with other models, the result shows that the model has the advantage of utilizing hidden information fully and analyzing the combination of components effectively. It is an important guide for measuring the trustworthiness measurement of component-based software. Reference | Related Articles | Metrics | Comments（0）

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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 （472）      PDF（pc） （2836KB）（316）       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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Predicting Stock Closing Price with Stock Network Public Opinion Based on AdaBoost-AAFSA-Elman Model and CEEMDAN Algorithm ZHU Changsheng1 (朱昶胜)，KANG Lianghe1.3* (康亮河)，FENG Wenfang2 (冯文芳) J Shanghai Jiaotong Univ Sci    2023, 28 (6): 809-821.   DOI: 10.1007/s12204-021-2337-x Abstract （315）      PDF（pc） （953KB）（312）       Knowledge map    Save To solve low prediction accuracy of Elman in predicting stock closing price, the model of adaptive boosting (AdaBoost)-improved artificial fish swarm algorithm (AAFSA)-Elman based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is proposed. By adding different white noise to the original data, CEEMDAN algorithm is used to decompose attributes serial selected by Boruta algorithm and text mining. To optimize the weight and threshold of Elman, self-adaption step length and view scope are used to improve artificial fish swarm algorithm (AFSA). AdaBoost algorithm is used to compose 5 weak AAFSA-Elman predictors into a strong predictor by continuous iteration. Experiments show that the mean absolute percentage error (MAPE) of AdaBoost-AAFSA-Elman model reduces from 4.9423% to 1.2338%. This study provides an experimental method for the prediction of stock closing price based on network public opinio. Reference | Related Articles | Metrics | Comments（0）

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Reward Function Design Method for Long Episode Pursuit Tasks Under Polar Coordinate in Multi-Agent Reinforcement Learning DONG Yubo1 (董玉博), CUI Tao1 (崔涛), ZHOU Yufan1 (周禹帆), SONG Xun2 (宋勋), ZHU Yue2 (祝月), DONG Peng1∗ (董鹏) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 646-655.   DOI: 10.1007/s12204-024-2713-4 Abstract （477）      PDF（pc） （567KB）（307）       Knowledge map    Save Multi-agent reinforcement learning has recently been applied to solve pursuit problems. However, it suffers from a large number of time steps per training episode, thus always struggling to converge effectively, resulting in low rewards and an inability for agents to learn strategies. This paper proposes a deep reinforcement learning (DRL) training method that employs an ensemble segmented multi-reward function design approach to address the convergence problem mentioned before. The ensemble reward function combines the advantages of two reward functions, which enhances the training effect of agents in long episode. Then, we eliminate the non-monotonic behavior in reward function introduced by the trigonometric functions in the traditional 2D polar coordinates observation representation. Experimental results demonstrate that this method outperforms the traditional single reward function mechanism in the pursuit scenario by enhancing agents’ policy scores of the task. These ideas offer a solution to the convergence challenges faced by DRL models in long episode pursuit problems, leading to an improved model training performance. Reference | Related Articles | Metrics | Comments（0）

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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 （208）      PDF（pc） （1691KB）（299）       Knowledge map    Save : Simulation of pedestrians’ behavior in the hub can help decision-makers to formulate better evacuation strategies. With this aim, this study develops an improved cellular automata model considering pedestrian’s mass-following psychology and competitive awareness, and based on this model, pedestrian’s evacuation process from the channel of the hub with two exits is simulated. Moreover, dynamic guidance information, e.g., the realtime congestion situation of the evacuation routes, plays an important role during pedestrian evacuation processes in a hub, as the evaluation routes can be adjusted based on this information. That is, the congestion situation during the evaluation can be improved. Thus, dynamic signs are incorporated into the proposed model to study the influence of dynamic guidance information on pedestrian evacuation behavior. In simulation experiments, the influence of two parameters, namely the proportion of pedestrians unfamiliar with the hub and update interval of dynamic signs, on pedestrian evacuation behavior is studied. Results show that dynamic guidance information can improve the efficiency of pedestrian evacuation. In particular, the higher the proportion of pedestrians unfamiliar with the hub is, the more obvious the effect of dynamic guidance information is. Besides, different proportions of pedestrians unfamiliar with the hub lead to different update intervals of dynamic signs. Finally, the results of this study can provide some implications to the practical hub operation and evacuation, e.g., to standardize the order of evacuation routes and improve the information service level in the hub. Reference | Related Articles | Metrics | Comments（0）

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Wind Speed Short-Term Prediction Based on Empirical Wavelet Transform, Recurrent Neural Network and Error Correction ZHU Changsheng(朱昶胜), ZHU Lina∗ (朱丽娜) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 297-308.   DOI: 10.1007/s12204-022-2477-7 Abstract （473）      PDF（pc） （1282KB）（290）       Knowledge map    Save Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy. However, owing to the stochastic and intermittent of wind speed, predicting wind speed accurately is difficult. A new hybrid deep learning model based on empirical wavelet transform, recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper. The empirical wavelet transformation is applied to decompose the original wind speed series. The long short term memory network and the Elman neural network are adopted to predict low-frequency and highfrequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy. The error correction strategy based on deep long short term memory network is developed to modify the prediction errors. Four actual wind speed series are utilized to verify the effectiveness of the proposed model. The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction. Reference | Related Articles | Metrics | Comments（0）

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Hysteresis Modeling and Compensation for Distal Shaft Deflection of Flexible Ureteroscope HUA Penga (华鹏)， SHU Xiongpenga (舒雄鹏)，XIE Lea,b* (谢叻) J Shanghai Jiaotong Univ Sci    2023, 28 (4): 507-.   DOI: 10.1007/s12204-022-2505-7 Abstract （336）      PDF（pc） （1652KB）（290）       Knowledge map    Save Flexible ureteroscopy (FURS) has been widely used in the diagnosis and treatment of upper urinarytract diseases. The key operation of FURS is that the surgeon manipulates the distal shaft of flexible ureteroscopeto a specific target for diagnosis and treatment. However, the hysteresis of flexible ureteroscope may be one ofthe most important factors that degrade the manipulation accuracy and the surgeon usually spends a long timenavigating the distal shaft during surgery. In this study, we obtained hysteresis curves of distal shaft deflectionfor the flexible ureteroscope through extensive repeated experiments. Then, two methods based on piecewiselinear approximation and long short-term memory neural network were employed to model the hysteresis curves.On this basis, we proposed two hysteresis compensation strategies for the distal shaft deflection. Finally, wecarried out hysteresis compensation experiments to verify the two proposed compensation strategies. Experimentalresults showed that the hysteresis compensation strategies can significantly improve position accuracy with meancompensation errors of no more than 5?. Reference | Related Articles | Metrics | Comments（0）

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AlgoTime-Varying Formation-Containment Tracking Control for Unmanned Aerial Vehicle Swarm Systems with Switching Topologies and a Non-Cooperative Target WU Xiaojing∗(武晓晶), CAO Tongyao (曹童瑶), ZHEN Ran (甄然), LI Zhijie (李志杰) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 689-701.   DOI: 10.1007/s12204-024-2728-x Abstract （448）      PDF（pc） （1627KB）（278）       Knowledge map    Save This paper studies the time-varying formation-containment tracking control problems for unmanned aerial vehicle (UAV) swarm systems with switching topologies and a non-cooperative target, where the UAV swarm systems consist of one tracking-leader, several formation-leaders, and followers. The formation-leaders are required to accomplish a predefined time-varying formation and track the desired trajectory of the tracking-leader, and the states of the followers should converge to the convex hull spanned by those of the formation-leaders. First, a formation-containment tracking protocol is proposed with the neighboring relative information, and the feasibilit condition for formation-containment tracking and the algebraic Riccati equation are given. Then, the stability of the control system with the designed control protocol is proved by constructing a reasonable Lyapunov function. Finally, the simulation examples are applied to verify the effectiveness of the theoretical results. The simulation results show that both the formation tracking error and the containment error are convergent, so the system can complete the formation containment tracking control well. In the actual battlefield, combat UAVs need to chase and attack hostile UAVs, but sometimes when multiple UAVs work together for military interception, formationcontainment tracking control will occur. Reference | Related Articles | Metrics | Comments（0）

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Ant Colony Algorithm Path Planning Based on Grid Feature Point Extraction LI Erchao∗ (李二超), QI Kuankuan (齐款款) J Shanghai Jiaotong Univ Sci    2023, 28 (1): 86-99.   DOI: 10.1007/s12204-023-2572-4 Abstract （518）      PDF（pc） （1196KB）（277）       Knowledge map    Save Aimed at the problems of a traditional ant colony algorithm, such as the path search direction and field of view, an inability to find the shortest path, a propensity toward deadlock and an unsmooth path, an ant colony algorithm for use in a new environment is proposed. First, the feature points of an obstacle are extracted to preprocess the grid map environment, which can avoid entering a trap and solve the deadlock problem. Second, these feature points are used as pathfinding access nodes to reduce the node access, with more moving directions to be selected, and the locations of the feature points to be selected determine the range of the pathfinding field of view. Then, based on the feature points, an unequal distribution of pheromones and a two-way parallel path search are used to improve the construction efficiency of the solution, an improved heuristic function is used to enhance the guiding role of the path search, and the pheromone volatilization coefficient is dynamically adjusted to avoid a premature convergence of the algorithm. Third, a Bezier curve is used to smooth the shortest path obtained. Finally, using grid maps with a different complexity and different scales, a simulation comparing the results of the proposed algorithm with those of traditional and other improved ant colony algorithms verifies its feasibility and superiority. 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 （872）      PDF（pc） （467KB）（276）       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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Arc and Droplet Behaviors in Horizontal Short-Arc Pulsed Gas Metal Arc Welding of 9%Ni Steel with ERNiCrMo-3 Welding Wire LIU Yiwei1 (刘轶玮), HUA Xueming1* (华学明), WU Dongsheng1 (吴东升), LI Fang1 (李芳), CAI Yan1 (蔡艳), WANG Huan2 (王欢), YANG Xiurong3 (杨修荣) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 361-376.   DOI: 10.1007/s12204-022-2548-9 Abstract （352）      PDF（pc） （5299KB）（271）       Knowledge map    Save Short-arc pulsed gas metal arc welding (P-GMAW) was used to solve the difficulties of molten pool spreading and droplet transfer of Ni-based welding wire. Suppression of short-circuit current was used to reduce spatter. Arc length stabilizer was used to acquire a proper and stable arc length maintained at the critical position where short circuit starts to occur. Short-arc P-GMAW with or without arc length stabilizer was compared. The droplet transfer, arc behaviors and weld bead profiles were investigated and compared based on the high-speed photography and observation of weld cross-section. When the arc length stabilizer was deactivated, the arc length was unstable and too short. The droplet transfer mode was mainly short circuit partial transfer, with only a small part of the droplet transferred into the molten pool, with the characteristics of no obvious necking, a few spatters, small droplet impact, long short circuit duration and high short-circuit current. There was also a small proportion of short circuit complete transfer with obvious necking, larger droplet impact, shorter short-circuit duration and lower short-circuit current. With arc length stabilizer, droplet transfer modes were short circuit complete transfer and spray transfer. The spray transfer had the largest droplet impact, no short circuit and no spatter. With the arc length stabilizer activated, a deep penetration, a high penetration ratio, a small reinforcement and a large reinforcement factor were acquired. This provides an innovative method to solve the difficulties of droplet transfer and molten pool spreading and eliminate the incomplete fusion in the GMAW of 9%Ni steel with nickel-based alloy welding wire. Reference | Related Articles | Metrics | Comments（0）

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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 （519）      PDF（pc） （1122KB）（263）       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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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 （602）      PDF（pc） （552KB）（257）       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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Improving Colonoscopy Polyp Detection Rate Using Semi-Supervised Learning YAO Leyul (姚乐宇)，HE Fan1,3 (何凡), PENG Haixia2* (彭海霞), WANG Xiaofeng2 (王晓峰)，ZHOU Lu2(周璐), HUANG Xiaolin1,3* (黄晓霖) J Shanghai Jiaotong Univ Sci    2023, 28 (4): 441-.   DOI: 10.1007/s12204-022-2519-1 Abstract （390）      PDF（pc） （497KB）（255）       Knowledge map    Save Colorectal cancer is one of the biggest health threats to humans and takes thousands of lives every year.Colonoscopy is the gold standard in clinical practice to inspect the intestinal wall, detect polyps and remove polypsin early stages, preventing polyps from becoming malignant and forming colorectal cancer instances. In recentyears, computer-aided polyp detection systems have been widely used in colonoscopies to improve the qualityof colonoscopy examination and increase the polyp detection rate. Currently, the most efficient computer-aidedsystems are built with machine learning methods. However, developing such a computer-aided detection systemrequires experienced doctors to label a large number of image data from colonoscopy videos, which is extremelytime-consuming, laborious and expensive. One possible solution is to adopt a semi-supervised learning, which canbuild a detection system on a dataset where part of its data is not necessary to be labeled. In this paper, on thebasis of state-of-the-art object detection method and semi-supervised learning technique, we design and implementa semi-supervised colonoscopy polyp detection system containing four main steps: running standard supervisedtraining with all labeled data; running inference on unlabeled data to obtain pseudo labels; applying a set ofstrong augmentation to both unlabeled data and pseudo label; combining labeled data, and unlabeled data withits pseudo labels to retrain the detector. The semi-supervised learning system is evaluated both on public datasetand our original private dataset and proves its effectiveness. Also, the inference speed of the semi-supervisedlearning system can meet the requirement of real-time operation. 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 （387）      PDF（pc） （1725KB）（255）       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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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 （202）      PDF（pc） （1537KB）（251）       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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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 （550）      PDF（pc） （194KB）（249）       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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Cross-Modal Entity Resolution for Image and Text Integrating Global and Fine-Grained Joint Attention Mechanism ZENG Zhirian(曾志贤),CAO Jianjun*(曹建军),WENG Nianfeng(翁年凤)，YUAN Zhen(袁震)，YU Xu(余旭) J Shanghai Jiaotong Univ Sci    2023, 28 (6): 728-737.   DOI: 10.1007/s12204-022-2465-y Abstract （291）      PDF（pc） （1951KB）（248）       Knowledge map    Save In order to solve the problem that the existing cross-modal entity resolution methods easily ignore the high-level semantic informational correlations between cross-modal data, we propose a novel cross-modal entity resolution for image and text integrating global and fine-grained joint attention mechanism method. First, we map the cross-modal data to a common embedding space utilizing a feature extraction network. Then, we integrate global joint attention mechanism and fine-grained joint attention mechanism, making the model have the ability to learn the global semantic characteristics and the local fine-grained semantic characteristics of the cross-modal data, which is used to fully exploit the cross-modal semantic correlation and boost the performance of cross-modal entity resolution. Moreover, experiments on Flickr-30K and MS-COCO datasets show that the overall performance of R@sum outperforms by 4.30% and 4.54% compared with 5 state-of-the-art methods, respectively, which can fully demonstrate the superiority of our proposed method. Reference | Related Articles | Metrics | Comments（0）

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CBF-Based Distributed Model Predictive Control for Safe Formation of Autonomous Mobile Robots MU Jianbin∗ (穆建彬), YANG Haili (杨海丽), HE Defeng (何德峰) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 678-688.   DOI: 10.1007/s12204-024-2747-7 Abstract （426）      PDF（pc） （969KB）（244）       Knowledge map    Save A distributed model predictive control (DMPC) method based on robust control barrier function (RCBF) is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment. The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivitymaintenance. RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements, and security constraints are achieved through a combination. Then, the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation. To ensure safe control, the optimization problem is integrated with the DMPC method. Finally, the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives. Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security. Reference | Related Articles | Metrics | Comments（0）

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Parameter Optimization and Precision Enhancement of Dual-Coil Eddy Current Sensor ZHANG Zhenning1(张振宁)，LIU Qiang2(刘强), Lü Chunfeng3(吕春峰)，MAO Yimeil(毛义梅)，TAo Weil(陶卫),ZHAO Huil*(赵辉) J Shanghai Jiaotong Univ Sci    2023, 28 (5): 596-603.   DOI: 10.1007/s12204-022-2511-9 Abstract （500）      PDF（pc） （948KB）（240）       Knowledge map    Save To enhance the measurement precision of eddy current sensor in particular environments such as extreme temperature changes and limited available space in aerospace, we optimized the structural parameters of the traditional dual-coil eddy current sensor probe by electromagnetic field analysis and finite element simulation modeling, and further presented the criteria for determining the optimal coil distance of the dual-coil probe. The simulation results are verified by setting up an experimental platform. For the extreme temperature environment, the displacement measurement error caused by the full range temperature variation of the dual-coil sensor under the optimal distance is less than 21.0% of that of the single-coil sensor. On this basis, we analyzed and verified the thermal stability of the structurally optimized dual-coil eddy current sensor. After temperature compensation, the displacement measurement accuracy can reach 14.9 times more accurate than that of the single-coil sensor. The method proposed in this paper can provide a design reference for the structural optimization of the axial dual-coil eddy current sensor probe. 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 （687）      PDF（pc） （1156KB）（237）       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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Numerical Study of Wave Energy Converter Platform Geometry Layout Design PEI Feia (裴斐), LIN Yanb∗ (林焰) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 780-790.   DOI: 10.1007/s12204-022-2483-9 Abstract （229）      PDF（pc） （2088KB）（229）       Knowledge map    Save The present work is aimed at determining the optimal geometry layout of a wave energy converter platform for plate energy harvesting performance. A linear potential fluid theory method was applied to analyzing the interaction between the platform and plate. Three factors of layout geometry were tested and the performance of the plate was analyzed. The methodology of design of experiments was used to confirm factor significance and build response surface model. The 1st order model and the 2nd order model were built to describe the relation between factors and plate performance. The significance of two factors and their interactions were revealed, and an optimal parameter set was found. The wave form in front of the plate confirmed the interactions. It is clear that a wide entrance and enclosing channel for waves can maximize the plate performance. Reference | Related Articles | Metrics | Comments（0）