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UAV Task Allocation for Hierarchical Multiobjective Optimization in Complex Conditions Using Modified NSGA-III with Segmented Encoding JIN Yudong (靳宇栋), FENG Jiabo (冯家波), ZHANG Weijun (张伟军) J Shanghai Jiaotong Univ Sci    2021, 26 (4): 431-445.   DOI: 10.1007/s12204-021-2269-5 Abstract （348）      PDF （2668KB）（292）       Knowledge map    With the recent boom in unmanned aerial vehicle (UAV) technology, many UAV applications involving complex and risky tasks in military and civilian fields have emerged, such as military strikes and disaster monitoring. Task allocation for UAVs is the process of planning the division of work among UAVs, controlled from ground stations by human operators. This study formulates the UAV task-allocation problem as an extended traveling salesman problem and presents a novel UAV task-allocation model for complex air concentration monitoring tasks. Then, an optimized non-dominated sorting genetic algorithm III (NSGA-III) based on a twin-exclusion mechanism, hierarchical objective-domination operator, and segmented gene encoding (i.e., NSGA-III-TEHOD) is developed to solve complex task-allocation problems involving multiple UAVs, hierarchical objectives, obstacles, and ambient wind. The algorithm is tested in several simulations, and the results demonstrate that the new algorithm outperforms NSGA-III, non-dominated sorting genetic algorithm II (NSGA-II), and genetic algorithm (GA) in terms of efficiency of global convergence and early maturation prevention and is available for the hierarchical objective-optimization problems. Reference | Related Articles | Metrics

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Eye Robotic System for Vitreoretinal Surgery DAI Qianlin (代倩琳), XU Mengqiao (徐梦乔), SUN Xiaodong (孙晓东), XIE Le∗ (谢叻) J Shanghai Jiaotong Univ Sci    2022, 27 (1): 1-6.   DOI: 10.1007/s12204-021-2369-2 Abstract （420）      PDF （1040KB）（247）       Knowledge map    Micro incision vitrectomy system (MIVS) is considered to be one of the most difficult tasks of eye surgery, due to its requirements of high accuracy and delicate operation under blurred vision environment. Therefore, robot-assisted ophthalmic surgery is a potential and efficient solution. Based on that consideration, a novel master-slave system for vitreoretinal surgery is realized. A 4-DOF remote center of motion (RCM) mechanism with a novel linear stage and end-effector is designed and the master-slave control system is implemented. The forward and inverse kinematics are analyzed for the controller implementation. Then, algorithms with motion scaling are also integrated into the control architecture for the purpose to enhance the surgeon’s operation accuracy. Finally, experiments on an eye model are conducted. The results show that the eye robotic system can fulfill surgeon’s motion following and simulate operation of vitrectomy, demonstrating the feasibility of this system. Reference | Related Articles | Metrics

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Medical Application of 3D Printing:A Powerful Tool for Personalised Treatment DAI Kerong (戴尅戎), XU Feng (许锋) J Shanghai Jiaotong Univ Sci    2021, 26 (3): 257-258.   DOI: 10.1007/s12204-021-2290-8 Abstract （489）      PDF （86KB）（199）       Knowledge map    We are in an era of technological revolutions promoting personalised healthcare. Advances in medical imaging techniques with 3D imaging software and 3D printing have allowed healthcare professionals to view and document various geometrical structures in a brand-new way, enabling them to make meaningful 3D measurements more accurately by generating both virtual and physical models used for preoperative planning,physician-patient communication, and fabrication of surgical guides, instruments, and implants[1-5]. With improvements in cost-effectiveness, efficiency, and mechanical properties, 3D printing technologies have become a powerful tool for physicians to meet clinical requirements. Furthermore, biological tissues made from 3D printing may eventually provide patients with required human organs in the future[6-7]. Although both medical communities and socialmedia spare no effort to highlight the prospects of 3D printing technologies in healthcare and popularise this innovative new method through Web-based approaches to promote its application in personalised treatment, to date, not a single healthcare organisation has yet released new technologies, disseminated findings in peerreviewed literature, or clarified the role and aims of 3D printing in healthcare. This, in turn, has left much of the current research and development to medical device companies, expecting them to meet individual clinical requests. Therefore, at present and in the future, it is critical to have a clear understanding of the clinical implementation of 3D printing for both traditional and personalised healthcare. The first step in the entire 3D printing process starts with medical imaging, in which professionals with expertise in radiology and imaging processing have conducted many investigations to identify and quantify patient-specific anatomical areas and geometrical structures before designing and manufacturing personalised medical models, surgical guides, medical instruments, and devices using 3D printing[8-11]. It must be noted that 3D printing usually starts with conventional clinical images, and errors cannot be avoided with several more complex steps involved in image processing. Traditionally,medical images have been acquired in radiology departments by trained radiologists using special software packages. With the help of commercial medical imaging processing software, such as MIMICS,Analyze, and MeDraw, many physicians from different specialties, with little engineering background, are able to perform these analyses by themselves and develop their preoperative planning software tailored to special medical treatments. Understandably, the development of software tailored to 3D printing needed in medicine could accelerate and promote its popularity in clinical practice. Organised by Journal of Shanghai Jiao Tong University (Science), this special issue, authored by a group of physicians and engineers with diverse and interdisciplinary backgrounds and insights, is intended to introduce their research topics in the most hotly debated areas where medical 3D printing is used in patient care,especially focusing on medical and dental applications. The issue also presents some related topics about imaging generation and processing, material properties, and biomechanics, among others. However, it is difficult to cover all the 3D printing fundamentals. In the current special issue, some interesting studies provide details regarding how to apply 3D printing to medical or dental personalised healthcare, which could be invaluable for physicians who would like to find their own methods of developing personalised routines by applying 3D printing in daily practice. The issue also includes some dedicated studies that focus on imaging and software applications, which are indispensable for those who are eager to enter the field of pre-processing in 3D printing. Last but not least, some studies discussing material properties and biomechanics with in-depth insights regarding the safety and reliability of 3D printing technology in the manufacturing of medical devices can be found in this issue. As authors and advocates of personalised treatment, we are interested in promoting 3D printing from its current niche applications to more widespread use in the medical community. Thus, this special issue also includes studies on some of these niche applications. Since 3D printing technology is now growing at an exponential rate, it is definitely a very challenging task to organise issues on 3D printing in personalised patient care. In this issue, we attempt to inspire our readers by choosing some clinical examples in several representative areas to show how 3D printing positively influences personalised healthcare. There is no doubt that 3D printing is truly one of the leading technologies of the 21st century and praised as a key feature of the fourth industrial revolution. We hope this special issue could provide essential information to help you understand the role that 3D printing plays in personalised patient care with the purpose of improving clinical outcomes and quality of life for patients in China and around the world. Finally, we genuinely hope that people with lofty ideals from both medical and engineering fields who are interested in 3D printing technologies notice this special issue and join us to enter the field with your meaningful contributions. Reference | Related Articles | Metrics

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Camera-Radar Fusion Sensing System Based on Multi-Layer Perceptron YAO Tong (姚 彤), WANG Chunxiang(王春香), QIAN Yeqiang(钱烨强) J Shanghai Jiaotong Univ Sci    2021, 26 (5): 561-568.   DOI: 10.1007/s12204-021-2345-x Abstract （288）      PDF （1189KB）（182）       Knowledge map    Environmental perception is a key technology for autonomous driving. Owing to the limitations of a single sensor, multiple sensors are often used in practical applications. However, multi-sensor fusion faces some problems, such as the choice of sensors and fusion methods. To solve these issues, we proposed a machine learning-based fusion sensing system that uses a camera and radar, and that can be used in intelligent vehicles. First, the object detection algorithm is used to detect the image obtained by the camera; in sequence, the radar data is preprocessed, coordinate transformation is performed, and a multi-layer perceptron model for correlating the camera detection results with the radar data is proposed. The proposed fusion sensing system was verified by comparative experiments in a real-world environment. The experimental results show that the system can effectively integrate camera and radar data results, and obtain accurate and comprehensive object information in front of intelligent vehicles. Reference | Related Articles | Metrics

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Sealing Performance of Pressure-Adaptive Seal LI Yuanfeng (李元丰), WANG Yiling (王怡灵), ZHANG Wanxin∗ (张万欣), LIU Jinian (刘冀念), MA Jialu (马加炉) J Shanghai Jiaotong Univ Sci    2022, 27 (6): 747-756.   DOI: 10.1007/s12204-022-2510-x Abstract （395）      PDF （2268KB）（161）       Knowledge map    A pressure-adaptive seal is developed to meet the demands of quick assembling and disassembling for an individual protection equipment in aerospace. The analysis model, which reflects the main characteristics of the seal structure, is built based on the finite element method and the Roth’s theory of rubber seal, and verified by the prototype test. The influences of precompression ratio, hardness of the sealing ring rubber, and friction coefficient on the sealing performance are investigated by variable parameter method. Results show that the model can describe the essential characteristics of the pressure-adaptive seal structure, which has good follow-up to the cavity pressure to achieve the purpose of pressure self-adaptive. The leakage rate correlates negatively with the precompression ratio of the sealing ring and the hardness of the sealing ring material, while is positively related to the friction coefficient between the sealing ring and the sealing edge. The maximum contact stress on sealing surface has negative correlation with the precompression ratio of the sealing ring, and positive correlation with the hardness of the seal ring material. The damage risk of the sealing ring increases with the increases of the precompression ratio of sealing ring, hardness of sealing ring material, and friction coefficient. Reference | Related Articles | Metrics

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Intelligent Connected Vehicle as the New Carrier Towards the Era of Connected World ZHUANG Hanyang (庄瀚洋), QIAN Yeqiang (钱烨强), YANG Ming(杨 明) J Shanghai Jiaotong Univ Sci    2021, 26 (5): 559-560.   Abstract （315）      PDF （83KB）（159）       Knowledge map    Human beings have been kept pursuing of higher efficiency and better safety to move people and things around since thousands of years ago. In modern soci-ety, vehicles are therefore invented and utilized to boost the speed and enhance the safety. In recent years, rapid development of information technology has brought hu-man into a new era of connected world. Internet and smartphones have made it extremely easy to get ac-cess to anyone from anywhere any time. In this back-ground, intelligent connected vehicles (ICVs) have been proposed and investigated. In the similar manner as the smartphones, ICVs are expected to be the next gener-ation carrier for people to get connected to the world. ICVs are equipped with novel sensors, controllers, and actuators to understand the environment, make decisions, and take actions, respectively. The word “intelligent” indicates that the vehicle should be able to handle unexpected events on the road. The word “connected” means that the information of each vehicle should be shared and considered globally. Full auton-omy and full connection are the ultimate goals of ICV industry. Unfortunately, we are still far away from this goal; therefore, continuous efforts shall be made to step further to this destination. As the ICV consists of multiple subsystems and is across different disciplines, the overall improvement re-quires the innovation in each aspect. Under this cir-cumstance, the Special Issue on Intelligent Connected Vehicle at Journal of Shanghai Jiao Tong University (Science) has been organized to broaden the perspec-tive, promote the interdisciplinary collaboration, and report the state-of-the-art works. Related Articles | Metrics

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Ventilation System Heating Demand Forecasting Based on Long Short-Term Memory Network ZHANG Zhanluo (张战罗), ZHANG Zhinan (张执南), EIKEVIK Trygve Magne, SMITT Silje Marie J Shanghai Jiaotong Univ Sci    2021, 26 (2): 129-137.   DOI: 10.1007/s12204-021-2277-5 Abstract （375）      PDF （1198KB）（146）       Knowledge map    Load forecasting can increase the efficiency of modern energy systems with built-in measuring systems by providing a more accurate peak power shaving performance and thus more reliable control. An analysis of an integrated CO2 heat pump and chiller system with a hot water storage system is presented in this paper. Drastic power fluctuations, which can be reduced with load forecasting, are found in historical operation records. A model that aims to forecast the ventilation system heating demand is thus established on the basis of a long short-term memory (LSTM) network. The model can successfully forecast the one-hour-ahead power using records of the past 48 h of the system operation data and the ambient temperature. The mean absolute percentage error (MAPE) of the forecast results of the LSTM-based model is 10.70%, which is respectively 2.2% and 7.25% better than the MAPEs of the forecast results of the support vector regression based and persistence method based models. Reference | Related Articles | Metrics

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Rethinking the Dice Loss for Deep Learning Lesion Segmentation in Medical Images ZHANG Yue (张月), LIU Shijie (刘世界), LI Chunlai (李春来), WANG Jianyu (王建宇) J Shanghai Jiaotong Univ Sci    2021, 26 (1): 93-102.   DOI: 10.1007/s12204-021-2264-x Abstract （483）      PDF （917KB）（135）       Knowledge map    Deep learning is widely used for lesion segmentation in medical images due to its breakthrough performance. Loss functions are critical in a deep learning pipeline, and they play important roles in segmenting performance. Dice loss is the most commonly used loss function in medical image segmentation, but it also has some disadvantages. In this paper, we discuss the advantages and disadvantages of the Dice loss function, and group the extensions of the Dice loss according to its improved purpose. The performances of some extensions are compared according to core references. Because different loss functions have different performances in different tasks, automatic loss function selection will be the potential direction in the future. Reference | Related Articles | Metrics

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Real-Time Trajectory Planning for On-road Autonomous Tractor-Trailer Vehicles SHEN Qiyue (沈琦越), WANG Bing (王 冰), WANG Chunxiang∗ (王春香) J Shanghai Jiaotong Univ Sci    2021, 26 (5): 722-730.   DOI: 10.1007/s12204-021-2362-9 Abstract （300）      PDF （1546KB）（126）       Knowledge map    Tractor-trailer vehicles, which are composed of a car-like tractor towing a passive trailer, have been widely deployed in the transportation industry, and trajectory planning is a critical step in enabling such a system to drive autonomously. Owing to the properties of being highly nonlinear and nonholonomic with complex dynamics, the tractor-trailer system poses great challenges to the development of motion-planning algorithms. In this study, an indirect trajectory planning framework for a tractor-trailer vehicle under on-road driving is presented to deal with the problem that the traditional planning framework cannot consider the feasibility and quality simultaneously in real-time trajectory generation of the tractor-trailer vehicle. The indirect planning framework can easily handle complicated tractor-trailer dynamics and generate high-quality, obstacle-free trajectory using quintic polynomial spline, speed pro?le optimization, forward simulation, and properly designed cost functions. Simulations under di?erent driving scenarios and trajectories with di?erent driving requirements are conducted to validate the performance of the proposed framework. Reference | Related Articles | Metrics

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Two Generative Design Methods of Hospital Operating Department Layouts Based on Healthcare Systematic Layout Planning and Generative Adversarial Network ZHAO Chaowang (赵朝望), YANG Jian (杨健), XIONG Wuyue (熊吴越), LI Jiatong (李佳潼) J Shanghai Jiaotong Univ Sci    2021, 26 (1): 103-115.   DOI: 10.1007/s12204-021-2265-9 Abstract （420）      PDF （1551KB）（121）       Knowledge map    With the increasing demands of health care, the design of hospital buildings has become increasingly demanding and complicated. However, the traditional layout design method for hospital is labor intensive, time consuming and prone to errors. With the development of artificial intelligence (AI), the intelligent design method has become possible and is considered to be suitable for the layout design of hospital buildings. Two intelligent design processes based on healthcare systematic layout planning (HSLP) and generative adversarial network (GAN) are proposed in this paper, which aim to solve the generation problem of the plane functional layout of the operating departments (ODs) of general hospitals. The first design method that is more like a mathematical model with traditional optimization algorithm concerns the following two steps: developing the HSLP model based on the conventional systematic layout planning (SLP) theory, identifying the relationship and flows amongst various departments/units, and arriving at the preliminary plane layout design; establishing mathematical model to optimize the building layout by using the genetic algorithm (GA) to obtain the optimized scheme. The specific process of the second intelligent design based on more than 100 sets of collected OD drawings includes: labelling the corresponding functional layouts of each OD plan; building image-to-image translation with conditional adversarial network (pix2pix) for training OD plane layouts, which is one of the most representative GAN models. Finally, the functions and features of the results generated by the two methods are analyzed and compared from an architectural and algorithmic perspective. Comparison of the two design methods shows that the HSLP and GAN models can autonomously generate new OD plane functional layouts. The HSLP layouts have clear functional area adjacencies and optimization goals, but the layouts are relatively rigid and not specific enough. The GAN outputs are the most innovative layouts with strong applicability, but the dataset has strict constraints. The goal of this paper is to help release the heavy load of architects in the early design stage and present the effectiveness of these intelligent design methods in the field of medical architecture. Reference | Related Articles | Metrics

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Biomechanical Analysis of Personalised 3D-Printed Clavicle Plates of Different Materials to Treat Midshaft Clavicle Fractures CHENG Rongshan, (程荣山), JIANG Ziang, (蒋子昂), DIMITRIOU Dimitris, GONG Weihua, (龚伟华), TSAI Tsung-Yuan, (蔡宗远) J Shanghai Jiaotong Univ Sci    2021, 26 (3): 259-266.   DOI: 10.1007/s12204-021-2291-7 Abstract （310）      PDF （1656KB）（120）       Knowledge map    This study was aimed at comparing the biomechanical performance of personalised 3D-printed clavicle  plates of different materials to treat midshaft clavicle fractures with the finite element (FE) method. The FE  model of a fractured clavicle with a personalised 3D-printed clavicle plate and screws was constructed. Three  types of materials were simulated, including stainless steel, titanium alloy, and magnesium alloy. Two loading  conditions (axial compression and inferior bending) were applied at the distal end of the clavicle to simulate arm  abduction. Plate stiffness, peak stress, and bone strain at the clavicle fracture site were measured and compared.  The stiffness of the stainless steel clavicle plate was significantly greater than that of the titanium alloy clavicle  plate. The stiffness of the magnesium alloy clavicle plate was similar to that of the intact clavicle; peak stress  of the magnesium alloy clavicle plate was the lowest; thus, it had less stress-shielding effects on bone formation.  The magnesium alloy clavicle plate was more likely to form bone by distributing proper strain at the clavicle  fracture site. According to the influence of different materials on the tensile strength, magnesium alloy clavicle  plates might be preferred owing to their bionic stiffness in the treatment of patients with a low risk of falling. For  patients who engage in contact sports, a titanium alloy clavicle plate might be more suitable. Reference | Related Articles | Metrics

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COVID-19 Interpretable Diagnosis Algorithm Based on a Small Number of Chest X-Ray Samples BU Ran (卜冉), XIANG Wei∗ (向伟), CAO Shitong (曹世同) J Shanghai Jiaotong Univ Sci    2022, 27 (1): 81-89.   DOI: 10.1007/s12204-021-2393-2 Abstract （279）      PDF （1470KB）（119）       Knowledge map    The COVID-19 medical diagnosis method based on individual’s chest X-ray (CXR) is achieved difficultly in the initial research, owing to difficulties in identifying CXR data of COVID-19 individuals. At the beginning of the study, infected individuals’ CXRs were scarce. The combination of artificial intelligence (AI) and medical diagnosis has been advanced and popular. To solve the difficulties, the interpretability analysis of AI model was used to explore the pathological characteristics of CXR samples infected with COVID-19 and assist in medical diagnosis. The dataset was expanded by data augmentation to avoid overfitting. Transfer learning was used to test different pre-trained models and the unique output layers were designed to complete the model training with few samples. In this study, the output results of four pre-trained models in three different output layers were compared, and the results after data augmentation were compared with the results of the original dataset. The control variable method was used to conduct independent tests of 24 groups. Finally, 99.23% accuracy and 98% recall rate were obtained, and the visual results of CXR interpretability analysis were displayed. The network of COVID-19 interpretable diagnosis algorithm has the characteristics of high generalization and lightweight. It can be quickly applied to other urgent tasks with insufficient experimental data. At the same time, interpretability analysis brings new possibilities for medical diagnosis. Reference | Related Articles | Metrics

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Solution to Long-Range Continuous and Precise Positioning in Deep Ocean for Autonomous Underwater Vehicles Using Acoustic Range Estimation and Inertial Sensor Measurements YANG Tao (杨 涛), ZHAO Jiankang∗ (赵健康) J Shanghai Jiaotong Univ Sci    2022, 27 (3): 281-297.   DOI: 10.1007/s12204-022-2441-6 Abstract （176）      PDF （2619KB）（115）       Knowledge map    Although advances in research into autonomous underwater vehicles (AUVs) have been made to extend their working depth and endurance, underwater experiments and missions remain to be restricted by the positioning performance of AUVs. With the Global Navigation Satellite System (GNSS) precluded due to the rapid attenuation of radio signals in underwater environments, acoustic positioning methods serve as an effective substitution. A long-range continuous and precise positioning solution for AUVs in deep ocean is proposed in this study, relying on acoustic signals from beacons at the same depth and aided by onboard inertial sensors. A signal system is investigated to provide time of arrival (TOA) estimation in a resolution of milliseconds. Without pre-knowledge or local measurement of the accurate sound speed, an AUV is enabled to continuously locate its horizontal position based on rough ranges estimated by an iterative least square (ILS) based algorithm. For better accuracy and robustness, range deviations are compensated with a reference point of known position and outliers in the trajectory are eliminated by an implementation of the extended Kalman filter (EKF) coupled with the state-acceptance filter. The solution is evaluated in simulation experiments with environmental information measured on the spot, providing an average position error from ground truth below 10 m with a standard deviation below 5 m. Reference | Related Articles | Metrics

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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 （268）      PDF （467KB）（107）       Knowledge map    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

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Advances in Medicine-Engineering Crossover in Automated Anesthesia XU Tianyi (徐天意), XIA Ming (夏明), JIANG Hong (姜虹) J Shanghai Jiaotong Univ Sci    2022, 27 (2): 137-143.   DOI: 10.1007/s12204-021-2329-x Abstract （249）      PDF （156KB）（102）       Knowledge map    Medicine-engineering crossover refers to the cross-fertilization of multiple disciplines to meet clinical needs through various means, including engineering, which greatly promotes medical development. In the development of anesthesiology, improvements in anesthesia equipment and continuous innovation of anesthesia technology are all closely related to the integration of medicine and engineering. In recent years, the exploration and development of automated anesthesia equipment has led to closer integration of medicine, engineering, and other disciplines, including the development of robots in anesthesia, automated monitoring and alarm technology,automated perioperative management, and remote anesthesia. Herein, the current status of applications and development of medicine-engineering crossover in the field of automated anesthesia are discussed. Reference | Related Articles | Metrics

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Collision-Free Path Planning with Kinematic Constraints in Urban Scenarios WANG Liang (王 亮), WANG Bing (王 冰), WANG Chunxiang∗ (王春香) J Shanghai Jiaotong Univ Sci    2021, 26 (5): 731-738.   DOI: 10.1007/s12204-021-2363-8 Abstract （247）      PDF （2199KB）（99）       Knowledge map    In urban driving scenarios, owing to the presence of multiple static obstacles such as parked cars and roadblocks, planning a collision-free and smooth path remains a challenging problem. In addition, the path-planning problem is mostly non-convex, and contains multiple local minima. Therefore, a method for combining a sampling-based method and an optimization-based method is proposed in this paper to generate a collision-free path with kinematic constraints for urban scenarios. The sampling-based method constructs a search graph to search for a seeding path for exploring a safe driving corridor, and the optimization-based method constructs a quadratic programming problem considering the desired state constraints, continuity constraints, driving corridor constraints, and kinematic constraints to perform path optimization. The experimental results show that the proposed method is able to plan a collision-free and smooth path in real time when managing typical urban scenarios. Reference | Related Articles | Metrics

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Automatic Removal of Multiple Artifacts for Single-Channel Electroencephalography ZHANG Chenbei (张晨贝), SABOR Nabil, LUO Junwen (罗竣文), PU Yu (蒲 宇), WANG Guoxing (王国兴), LIAN Yong∗ (连 勇) J Shanghai Jiaotong Univ Sci    2022, 27 (4): 437-451.   DOI: 10.1007/s12204-021-2374-5 Abstract （190）      PDF （2934KB）（98）       Knowledge map    Removing different types of artifacts from the electroencephalography (EEG) recordings is a critical step in performing EEG signal analysis and diagnosis. Most of the existing algorithms aim for removing single type of artifacts, leading to a complex system if an EEG recording contains different types of artifacts. With the advancement in wearable technologies, it is necessary to develop an energy-efficient algorithm to deal with different types of artifacts for single-channel wearable EEG devices. In this paper, an automatic EEG artifact removal algorithm is proposed that effectively reduces three types of artifacts, i.e., ocular artifact (OA), transmission- line/harmonic-wave artifact (TA/HA), and muscle artifact (MA), from a single-channel EEG recording. The effectiveness of the proposed algorithm is verified on both simulated noisy EEG signals and real EEG from CHB- MIT dataset. The experimental results show that the proposed algorithm effectively suppresses OA, MA and TA/HA from a single-channel EEG recording as well as physical movement artifact. Reference | Related Articles | Metrics

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Influence of Thermal Modification on Al-Si Coating of Hot-Stamped 22MnB5 Steel: Microstructure, Phase Transformation, and Mechanical Properties WANG Qiongyan (王琼燕), LIN Wenhu (林文虎),LI Fang∗ (李芳), SHEN Chen (沈忱), HUA Xueming (华学明) J Shanghai Jiaotong Univ Sci    2021, 26 (6): 747-756.   DOI: 10.1007/s12204-021-2267-7 Abstract （239）      PDF （3340KB）（96）       Knowledge map    The hot-stamped steel with ultrahigh strength is a promising material for the fabrication of automotivecomponents. However, the coating on the sheet surface leads to a softening problem in the welded joint. Instead ofthe costly coating removal process, heat treatment is an economical and effective method for the diffusion process,which can decrease the Al concentration in the coating. In this study, a preheating treatment was carried out onAl-Si-coated 22MnB5 hot-stamped steels for the homogeneity of Al, followed by laser welding and hot stamping.The effects of the preheating on the microstructure and mechanical properties of the laser-welded joints wereinvestigated. With the preheating treatment, the Al-Si coating transformed into an Fe-Al intermetallic compoundand the difference in Al content between the coating and substrate was reduced. The Al content in the weld ofthe specimen with the preheating treatment was reduced, compared with that without the preheating treatment.The amount of δ-ferrite in the weld after laser welding was reduced largely. The distribution of long-bland-likesegregation was changed to a fine and uniform distribution. With the preheating treatment, the tensile strengthof the welded joint was significantly improved and comparable to that of the decoated joint. In conclusion, thepreheating treatment before the welding is an effective method to suppress the formation of δ-ferrite and improvethe mechanical properties of the welded joint. Reference | Related Articles | Metrics

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Using a Patient-Specific 3D-Printed Surgical Guide for High Tibial Osteotomy: A Technical Note JIANG Xu, (江旭), XIE Kai (谢凯), LI Bo (李波), HU Xumin (胡旭民), WU Haishan (吴海山), GAO Liangbin (高梁斌), WANG Liao (王燎), YAN Mengning (严孟宁) J Shanghai Jiaotong Univ Sci    2021, 26 (3): 339-345.   DOI: 10.1007/s12204-021-2302-8 Abstract （258）      PDF （1004KB）（95）       Knowledge map    Patient-specific instrumentation (PSI) enables a more accurate alignment of the lower limbs in a high  tibial osteotomy (HTO) than in traditional surgery; however, the current design of commercial PSIs is not perfect.  Therefore, we designed a new patient-specific surgical guide to improve the accuracy of the osteotomy and verified  its reliability through a clinical operation. Here, we describe a patient with isolated medial-compartment bilateral  knee osteoarthritis, accompanied by a varus deformity of the proximal tibia. The patient was treated with HTO  using a patient-specific 3D-printed surgical guide. We concluded that the patient-specific 3D-printed surgical  guide improved the accuracy of the osteotomy and the alignment of the lower limb.  Reference | Related Articles | Metrics

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Physical Characterization of Ionic Liquid-Modified Polyvinyl Alcohol and Sodium Thiocyanate Polymer Electrolytes for Electrochemical Double-Layer Capacitor Application AZEMTSOP Manfo Theodore , MEHRA Ram Mohan , KUMAR Yogesh , GUPTA Meenal J Shanghai Jiaotong Univ Sci    2023, 28 (2): 161-171.   DOI: 10.1007/s12204-021-2397-y Abstract （235）      PDF （1140KB）（94）       Knowledge map    Novel gel polymer electrolytes (GPEs) composed of polyvinyl alcohol (PVA) and sodium thiocyanate were developed via a solution casting technique. An ionic liquid (IL), 1-ethyl-3-methyl-imidazolium tricyanomethanide ([EMIM][TCM]), was doped into a polymer–salt complex system (PVA + NaSCN) to further enhance the conductivity. IL-doped polymer electrolyte (ILDPE) films were characterized using X-ray diffraction (XRD), polarized optical microscopy (POM), Fourier-transform infrared (FTIR) spectroscopy, and conductivity measurements. XRD was performed to check the degree of crystallinity and amorphicity of the ILDPE films, and the amorphicity of GPEs increased with the increase of the IL content. POM was employed to evaluate the changes in the surface morphology due to the inclusion of salt and IL in the PVA. The compositional nature of the GPE films was examined via FTIR studies. The electrical and electrochemical properties were characterized by cyclic voltammetry and electrochemical impedance spectroscopy. The maximum conductivity for the GPE film was estimated to be 1.10 × 10-5 S/cm for 6% (mass fraction) of IL in the polymer–salt complex. The ionic transference number was approximately 0.97. An electrochemical double-layer capacitor (EDLC) was built from optimized GPE films and reduced graphene oxide-based electrodes. The specific capacitance calculated from the cyclic voltammograms of the EDLC cells was 3 F/g. Reference | Related Articles | Metrics

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Adaptive Human-Robot Collaboration Control Based on Optimal Admittance Parameters YU Xinyi (禹鑫燚), WU Jiaxin (吴加鑫), XU Chengjun (许成军), LUO Huizhen (罗惠珍), OU Linlin∗ (欧林林) J Shanghai Jiaotong Univ Sci    2022, 27 (5): 589-601.   DOI: 10.1007/s12204-022-2460-3 Abstract （224）      PDF （1674KB）（91）       Knowledge map    In order to help the operator perform the human-robot collaboration task and optimize the task performance, an adaptive control method based on optimal admittance parameters is proposed. The overall control structure with the inner loop and outer loop is first established. The tasks of the inner loop and outer loop are robot control and task optimization, respectively. Then an inner-loop robot controller integrated with barrier Lyapunov function and radial basis function neural networks is proposed, which makes the robot with unknown dynamics securely behave like a prescribed robot admittance model sensed by the operator. Subsequently, the optimal parameters of the robot admittance model are obtained in the outer loop to minimize the task tracking error and interaction force. The optimization problem of the robot admittance model is transformed into a linear quadratic regulator problem by constructing the human-robot collaboration system model. The model includes the unknown dynamics of the operator and the task performance details. For relaxing the requirement of the system model, the integral reinforcement learning is employed to solve the linear quadratic regulator problem. Besides, an auxiliary force is designed to help the operator complete the specific task better. Compared with the traditional control scheme, the security performance and interaction performance of the human-robot collaboration system are improved. The effectiveness of the proposed method is verified through two numerical simulations. In addition, a practical human-robot collaboration experiment is carried out to demonstrate the performance of the proposed method. Reference | Related Articles | Metrics

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Application of Digital Medicine in Addiction WU Xiaojun (吴萧俊), DU Jiang (杜江), JIANG Haifeng (江海峰), ZHAO Min (赵敏) J Shanghai Jiaotong Univ Sci    2022, 27 (2): 144-152.   DOI: 10.1007/s12204-021-2391-4 Abstract （213）      PDF （185KB）（85）       Knowledge map    Digital medicine plays an important role in disease assessment, psychological intervention, and relapse management in mental illnesses. Patients with substance use disorders can be easily affected by the environment and negative emotions, inducing addiction and relapse. However, due to social discrimination, stigma, or economic issues, they are unwilling to go to the hospital for treatment, making it difficult for health workers to track their health changes. Additionally, mental health resources in China are insufficient. Digital medicine aims to solve these problems. This article reviews digital medicine in the field of addiction, hoping to provide a reference for the future exploration of more individualized and effective digital medicine. Reference | Related Articles | Metrics

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Parameter Identification of Magic Formula Tire Model Based on Fibonacci Tree Optimization Algorithm FENG Shilin (冯世林), ZHAO Youqun (赵又群), DENG Huifan (邓汇凡), WANG Qiuwei(王秋伟), CHEN Tingting (陈婷婷) J Shanghai Jiaotong Univ Sci    2021, 26 (5): 647-657.   DOI: 10.1007/s12204-021-2354-9 Abstract （260）      PDF （1130KB）（85）       Knowledge map    The magic formula (MF) tire model is a semi-empirical tire model that can precisely simulate tire behavior. The heuristic optimization algorithm is typically used for parameter identification of the MF tire model. To avoid the defect of the traditional heuristic optimization algorithm that can easily fall into the local optimum, a parameter identification method based on the Fibonacci tree optimization (FTO) algorithm is proposed, which is used to identify the parameters of the MF tire model. The proposed method establishes the basic structure of the Fibonacci tree alternately through global and local searches and completes optimization accordingly. The global search rule in the original FTO was modified to improve its efficiency. The results of independent repeated experiments on two typical multimodal function optimizations and the parameter identification results showed that FTO was not sensitive to the initial values. In addition, it had a better global optimization performance than genetic algorithm (GA) and particle swarm optimization (PSO). The root mean square error values optimized with FTO were 5.09%, 10.22%, and 3.98% less than the GA, and 6.04%, 4.47%, and 16.42% less than the PSO in pure lateral and longitudinal forces, and pure aligning torque parameter identi?cation. The parameter identification method based on FTO was found to be effective. Reference | Related Articles | Metrics

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Effect of Deflectors on the Flow Characteristics of a Square Pipe with a 90° Bend JIANG Chenqi (江晨琦), GONG Zhaoxin (宫兆新) J Shanghai Jiaotong Univ Sci    2021, 26 (2): 163-169.   DOI: 10.1007/s12204-021-2278-4 Abstract （326）      PDF （2608KB）（85）       Knowledge map    Pipe flow is a classic hydrodynamic issue. Most pipelines contain bends, and bends cause energy loss and distort the flow because of secondary flow. Deflectors are often used to adjust the flow quality in a bend. In this study, a numerical simulation using ANSYS Fluent 19.0 is used to analyze the effects of the deflector number, location and angle on the flow characteristics of a square pipe with a 90° bend. The velocity non-uniformity and the head loss are analyzed quantitatively. The secondary flow is presented visually, and its evolution characteristics are assessed. An optimized installation scheme for the deflectors is discussed, and a reference is provided for controlling the flow quality in bends via deflectors. Reference | Related Articles | Metrics

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Velocity-Varying Target Tracking of Mobile Sensor Network Based on Flocking Control ZHANG Lulu (章露露), DONG Xiangxiang (董祥祥), YAO Lixiu (姚莉秀), CAI Yunze (蔡云泽) J Shanghai Jiaotong Univ Sci    2021, 26 (4): 446-453.   DOI: 10.1007/s12204-021-2283-7 Abstract （298）      PDF （481KB）（83）       Knowledge map    Existing coupled distributed estimation and motion control strategies of mobile sensor networks present limitations in velocity-varying target tracking. Therefore, a velocity-varying target tracking algorithm based on flocking control is proposed herein. The Kalman-consensus filter is utilized to estimate the position, velocity and acceleration of a target. The flocking control algorithm with a velocity-varying virtual leader enables the position of the center of the mobile sensor network to converge to that of the target. By applying an effective cascading Lyapunov method, stability analysis is performed. Simulation results are provided to validate the feasibility of the proposed algorithm. Reference | Related Articles | Metrics

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Wavelet Transform-Based High-Definition Map Construction From a Panoramic Camera ZHUANG Hanyang (庄瀚洋), ZHOU Xuejun (周学军), WANG Chunxiang (王春香), QIAN Yuhan (钱宇晗) J Shanghai Jiaotong Univ Sci    2021, 26 (5): 569-576.   DOI: 10.1007/s12204-021-2346-9 Abstract （222）      PDF （1242KB）（82）       Knowledge map    High-definition (HD) maps are key components that provide rich topologic and semantic information for decision-making in vehicle autonomous driving systems. A complete ground orthophoto is usually used as the base image to construct the HD map. The ground orthophoto is obtained through inverse perspective transformation and image mosaicing. During the image mosaicing, multiple consecutive orthophotos are stitched together using pose information and image registration. In this study, wavelet transform is introduced to the image mosaicing process to alleviate the information loss caused by image overlapping. In the orthophoto wavelet transform, high-frequency and low-frequency components are fused using different strategies to form a complete base image with clearer local details. Experimental results show that the accuracy of the orthophotos generated using this method is improved. Reference | Related Articles | Metrics

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Safety Protection Method of Rehabilitation Robot Based on fNIRS and RGB-D Information Fusion LI Dong (李栋), FAN Yulin (樊钰琳), L v Na (吕娜), CHEN Guodong∗ (陈国栋), WANG Zheng (王正), CHI Wenzheng (迟文政) J Shanghai Jiaotong Univ Sci    2022, 27 (1): 45-54.   DOI: 10.1007/s12204-021-2365-6 Abstract （233）      PDF （2503KB）（82）       Knowledge map    In order to improve the safety protection performance of the rehabilitation robot, an active safety protection method is proposed in the rehabilitation scene. The oxyhemoglobin concentration information and RGB-D information are combined in this method, which aims to realize the comprehensive monitoring of the invasion target, the patient’s brain function movement state, and the joint angle in the rehabilitation scene. The main focus is to study the fusion method of the oxyhemoglobin concentration information and RGB-D information in the rehabilitation scene. Frequency analysis of brain functional connectivity coefficient was used to distinguish the basic motion states. The human skeleton recognition algorithm was used to realize the angle monitoring of the upper limb joint combined with the depth information. Compared with speed and separation monitoring, the protection method of multi-information fusion is safer and more comprehensive for stroke patients. By building the active safety protection platform of the upper limb rehabilitation robot, the performance of the system in different safety states is tested, and the safety protection performance of the method in the upper limb rehabilitation scene is verified. Reference | Related Articles | Metrics

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Further Result on the Observer Design for One-Sided Lipschitz Systems YANG Ming1 (杨 明), HUANG Jun1∗ (黄 俊), ZHANG Wei2 (章 伟) J Shanghai Jiaotong Univ Sci    2022, 27 (6): 817-822.   DOI: 10.1007/s12204-020-2252-6 Abstract （142）      PDF （328KB）（80）       Knowledge map    This paper investigates the problem of observer design for a class of control systems. Different from current works, the nonlinear functions in the system only satisfy the property of the one-sided Lipschitz (OSL) condition but not quadratic inner-boundedness (QIB). Moreover, the case where the OSL constant is negative is specially investigated. Firstly, a full-order observer is constructed for the original system. Then, a reduced-order observer is also designed by using the decomposition method. The advantage and effectiveness of the proposed design scheme are shown in a numerical simulation. Reference | Related Articles | Metrics

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Developing High-Precision Maps for Automated Driving in China: Legal Obstacles and the Way to Overcome Them ZHANG Taolue∗ (张韬略), TU Huizhao (涂辉招), QIU Wei (邱 炜) J Shanghai Jiaotong Univ Sci    2021, 26 (5): 658-669.   DOI: 10.1007/s12204-021-2355-8 Abstract （192）      PDF （285KB）（79）       Knowledge map    A high-precision map (HPM) is the key infrastructure to realizing the function of automated driving (AD) and ensuring its safety. However, the current laws and regulations on HPMs in China can lead to serious legal compliance problems. Thus, proper measures should be taken to remove these barriers. Starting with a complete view of the current legal obstacles to HPMs in China, this study first explains why these legal obstacles exist and the types of legal interests they are trying to protect. It then analyzes whether new technology could be used as an alternative to resolve these concerns. Factors such as national security, AD industry needs, and personal data protection, as well as the ?exibility of applying technology, are discussed and analyzed hierarchically for this purpose. This study proposes that China should adhere to national security and AD industry development, pass new technical regulations that redefine the scope of national security regarding geographic information in the field of HPMs, and establish a national platform under the guidance and monitoring of the government to integrate scattered resources and promote the development of HPMs via crowdsourcing. Regarding the legal obstacles with higher technical plasticity, priority should be given to technical solutions such as “available but invisible” technology. Compared with the previous research, this study reveals the current legal barriers in China that have different levels of relevance to national security and different technical plasticity. It also proposes original measures to remove them, such as coordinating national security with the development of the AD industry, reshaping the boundary of national security and industrial interests, and giving priority to technical solutions for legal barriers that have strong technical plasticity. Reference | Related Articles | Metrics

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3D Printing Bioink Preparation and Application in Cartilage Tissue Reconstruction in Vitro SUN Binbin (孙彬彬), HAN Yu (韩煜), JIANG Wenbo (姜闻博), DAI Kerong(戴尅戎) J Shanghai Jiaotong Univ Sci    2021, 26 (3): 267-271.   DOI: 10.1007/s12204-021-2292-6 Abstract （305）      PDF （1061KB）（79）       Knowledge map    Three-dimensional (3D) bioprinting technology has great potential for application in the treatment  of cartilage defects. However, the preparation of biocompatible and stable bioinks is still a major challenge. In  this study, decellularized extracellular matrix (dECM) of soft tissue was used as the basic material to prepare the  bioink. Our results showed that this novel dECM-derived bioink had good printing performance and comprised  a large number of fine nanofibers. Biological characterization revealed that the bioink was compatible with the  growth of chondrocytes and that the nanofibrous structure greatly promoted cell proliferation. Histological and  immunohistochemical analyses showed that the in vitro printed cartilage displayed the presence of characteristic  cartilage lacunae. Thus, a new preparation method for dECM-derived bioink with potential application in generation  of cartilage was developed in this study. Reference | Related Articles | Metrics

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Review on Corrosion Characteristics of Porous Titanium Alloys Fabricated by Additive Manufacturing GAI Xin, (盖欣), BAI Yun (白芸), LI Shujun (李述军), WANG Liao (王燎), AI Songtao (艾松涛), HAO Yulin (郝玉琳), YANG Rui (杨锐), DAI Kerong (戴尅戎) J Shanghai Jiaotong Univ Sci    2021, 26 (3): 416-430.   DOI: 10.1007/s12204-021-2314-4 Abstract （216）      PDF （1891KB）（79）       Knowledge map    Porous titanium and its alloys have been considered as promising implants owing to their low elastic  modulus and capability to provide channels for bone growth. Currently, additive manufacturing (3D printing)  techniques have been successfully applied to produce porous titanium alloys owing to the advantages of controllable  and precise fabrication. Considering the safety aspect, an understanding of corrosion in porous titanium alloys  and the corresponding mechanisms is important for their long-term application in the human body. In this  paper, the recent progress in improving the corrosion properties of porous titanium alloys fabricated via 3D  printing techniques is reviewed. The effects of pore type, porosity, electrolyte, and modification of the material  on the corrosion properties of porous titanium alloys are introduced and discussed. In addition, the limitations of  traditional methods for measuring the corrosion performance of porous titanium alloys were analysed. Perspectives  for evaluating and improving the corrosion performance of porous titanium alloys using new methods are provided.  Reference | Related Articles | Metrics

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Development of a Robotic Cochlear Implantation System CHEN Ziyun (陈子云), XIE Le (谢叻), DAI Peidong (戴培东), ZHANG Tianyu (张天宇) J Shanghai Jiaotong Univ Sci    2022, 27 (1): 7-14.   DOI: 10.1007/s12204-021-2381-6 Abstract （313）      PDF （1384KB）（78）       Knowledge map    Traditional cochlear implantation surgery has problems such as high surgical accuracy requirement and large trauma, which cause the difficulty of the operation and the high requirements for doctors, so that only a few doctors can complete the operation independently. However, there is no research on robotic cochlear implantation in China. In response to this problem, a robotic cochlear implantation system is proposed. The robot is controlled by robot operating system (ROS). A simulation environment for the overall surgery is established on the ROS based on the real surgery environment. Through the analysis of the kinematics and the motion planning algorithm of the manipulator, an appropriate motion mode is designed to control the motion of the manipulator, and perform the surgery under the simulation environment. A simple and feasible method of navigation is proposed, and through the model experiment, the feasibility of robotic cochlear implantation surgery is verified. Reference | Related Articles | Metrics

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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 （134）      PDF （1196KB）（77）       Knowledge map    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

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Airframe Damage Region Division Method Based on Structure Tensor Dynamic Operator CAI Shuyu∗ (蔡舒妤), SHI Lizhong (师利中) J Shanghai Jiaotong Univ Sci    2022, 27 (6): 757-767.   DOI: 10.1007/s12204-022-2498-2 Abstract （191）      PDF （1607KB）（76）       Knowledge map    In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region, the airframe damage region division method based on the structure tensor dynamic operator is proposed in this paper. The structure tensor feature space is established to represent the local features of damage images. It makes different damage images have the same feature distribution, and transform varied damage region division into consistent process of feature space division. On this basis, the structure tensor dynamic operator generation method is designed. It integrates with bacteria foraging optimization algorithm improved by defining double fitness function and chemotaxis rules, in order to calculate the parameters of dynamic operator generation method and realize the structure tensor feature space division. And then the airframe damage region division is realized. The experimental results on different airframe structure damage images show that compared with traditional threshold division method, the proposed method can improve the division quality. The interference of damage adjacent region is eliminated. The information loss caused by over-segmentation is avoided. And it is efficient in operation, and consistent in process. It also has the applicability to different types of structural damage. Reference | Related Articles | Metrics

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Multi-Object Tracking Strategy of Autonomous Vehicle Using Modified Unscented Kalman Filter and Reference Point Switching WANG Muyuan∗ (王木塬), WU Xiaodong (吴晓东) J Shanghai Jiaotong Univ Sci    2021, 26 (5): 607-614.   DOI: 10.1007/s12204-021-2350-0 Abstract （256）      PDF （1070KB）（75）       Knowledge map    In this study, a multi-object tracking (MOT) scheme based on a light detection and ranging sensor was proposed to overcome imprecise velocity observations in object occlusion scenarios. By applying real-time velocity estimation, a modified unscented Kalman filter (UKF) was proposed for the state estimation of a target object. The proposed method can reduce the calculation cost by obviating unscented transformations. Additionally, combined with the advantages of a two-reference-point selection scheme based on a center point and a corner point, a reference point switching approach was introduced to improve tracking accuracy and consistency. The state estimation capability of the proposed UKF was verified by comparing it with the standard UKF in single-target tracking simulations. Moreover, the performance of the proposed MOT system was evaluated using real traffic datasets. Reference | Related Articles | Metrics

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Numerical Study of Sodium Bentonite Extrusion into a Planar Fracture LIU Miaomiao (刘苗苗), LI Xiaoyue (李晓月), XU Yongfu (徐永福) J Shanghai Jiaotong Univ Sci    2021, 26 (2): 146-154.   DOI: 10.1007/s12204-021-2268-6 Abstract （253）      PDF （940KB）（75）       Knowledge map     As a candidate buffer/backfill material for high-level radioactive waste geological repositories, bentonite has numerous favorable properties, such as low permeability, high expansibility, and a high sorption capacity for radionuclides. The radionuclide-isolating performance of a buffer is strongly influenced by its extrusion. In this study, the bentonite extrusion process is explored: its basic mechanism can be considered free swelling of the bentonite. A 2D extrusion model of bentonite that is based on the 1D free swelling model of bentonite is presented. A numerical method is proposed to investigate the extrusion process of Na-bentonite into fractures over time under no-seepage conditions based on the free swelling model. The influences of the electrolyte concentration and dry density on the extrusion depth and mass of the bentonite are discussed, and the distribution of montmorillonite inside the bentonite is analysed. The rationale of the proposed bentonite extrusion model is then illustrated in comparison with the results of the bentonite extrusion test. Reference | Related Articles | Metrics

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Word Embedding Bootstrapped Deep Active Learning Method to Information Extraction on Chinese Electronic Medical Record MA Qunsheng (马群圣), CEN Xingxing (岑星星), YUAN Junyi (袁骏毅), HOU Xumin (侯旭敏) J Shanghai Jiaotong Univ Sci    2021, 26 (4): 494-502.   DOI: 10.1007/s12204-021-2285-5 Abstract （272）      PDF （696KB）（74）       Knowledge map     Electronic medical record (EMR) containing rich biomedical information has a great potential in disease diagnosis and biomedical research. However, the EMR information is usually in the form of unstructured text, which increases the use cost and hinders its applications. In this work, an effective named entity recognition (NER) method is presented for information extraction on Chinese EMR, which is achieved by word embedding bootstrapped deep active learning to promote the acquisition of medical information from Chinese EMR and to release its value. In this work, deep active learning of bi-directional long short-term memory followed by conditional random field (Bi-LSTM+CRF) is used to capture the characteristics of different information from labeled corpus, and the word embedding models of contiguous bag of words and skip-gram are combined in the above model to respectively capture the text feature of Chinese EMR from unlabeled corpus. To evaluate the performance of above method, the tasks of NER on Chinese EMR with “medical history” content were used. Experimental results show that the word embedding bootstrapped deep active learning method using unlabeled medical corpus can achieve a better performance compared with other models. Reference | Related Articles | Metrics

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Improvement of Physical Fitness Test Assessment Criteria Based on fNIRS Technology: Taking Pull-Up as an Example GONG Bin(巩斌), YU Xianghua(禹香华), FANG Yu (方宇), WANG Zheng (王正), YANG Hao (杨皓), CHEN Guodong (陈国栋), L Ü Na (吕娜) J Shanghai Jiaotong Univ Sci    2022, 27 (2): 219-225.   DOI: 10.1007/s12204-021-2367-4 Abstract （169）      PDF （1855KB）（74）       Knowledge map    Pull-up, as an important physical fitness test event of the “National Student Physical Health Standard”, is known as a difficult physical fitness test event. To improve the assessment criteria of pull-ups, this paper uses the functional near-infrared spectroscopy (fNIRS) to monitor the changes and activation of oxyhemoglobin (HbO) signals in the brain motor cortex of people with different body mass indexes (BMIs) during the pullup assessment. Then the relationship between BMIs and evaluation criteria is discussed. After collecting and analyzing experimental data of 18 recruited college students, it is found that the number of pull-ups performed by people with different BMIs is different when they reach the peak state of brain activation. The results of the study indicate that different assessment criteria should be adopted for different BMI groups. It is suggested that the BMI should be introduced as one of the test indexes in the examination of pull-ups event in “National Student Physical Health Standard”. Reference | Related Articles | Metrics

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SeRN: A Two-Stage Framework of Registration for Semi-Supervised Learning for Medical Images JIA Dengqiang* (贾灯强), LUO Xinzhe (罗鑫喆), DING Wangbin (丁王斌),HUANG Liqin (黄立勤), ZHUANG Xiahai (庄吓海) J Shanghai Jiaotong Univ Sci    2022, 27 (2): 176-189.   DOI: 10.1007/s12204-021-2383-4 Abstract （146）      PDF （2406KB）（72）       Knowledge map    Significant breakthroughs in medical image registration have been achieved using deep neural networks (DNNs). However, DNN-based end-to-end registration methods often require large quantities of data or adequate annotations for training. To leverage the intensity information of abundant unlabeled images, unsupervised registration methods commonly employ intensity-based similarity measures to optimize the network parameters.However, finding a sufficiently robust measure can be challenging for specific registration applications. Weakly supervised registration methods use anatomical labels to estimate the deformation between images. High-level structural information in label images is more reliable and practical for estimating the voxel correspondence of anatomic regions of interest between images, whereas label images are extremely difficult to collect. In this paper, we propose a two-stage semi-supervised learning framework for medical image registration, which consists of unsupervised and weakly supervised registration networks. The proposed semi-supervised learning framework is trained with intensity information from available images, label information from a relatively small number of labeled images and pseudo-label information from unlabeled images. Experimental results on two datasets (cardiac and abdominal images) demonstrate the efficacy and efficiency of this method in intra- and inter-modality medical image registrations, as well as its superior performance when a vast amount of unlabeled data and a small set of annotations are available. Our code is publicly available at https://github.com/jdq818/SeRN. Reference | Related Articles | Metrics

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Fabrication and Performance Investigation of Karma Alloy Thin Film Strain Gauge LEI Peng (雷鹏), ZHANG Congchun (张丛春), PANG Yawen (庞雅文), YANG Shenyong (杨伸勇), ZHANG Meiju (张梅菊) J Shanghai Jiaotong Univ Sci    2021, 26 (4): 454-462.   DOI: 10.1007/s12204-021-2315-3 Abstract （267）      PDF （1164KB）（72）       Knowledge map    Karma alloy thin film strain gauges were fabricated on alumina substrates by magnetron sputtering. The electrical properties of strain gauges annealed at different temperatures were then tested. The surface morphology and phase structure of the Karma alloy thin films were analyzed using X-ray diffraction and scanning electron microscopy. The effect of the annealing temperature on the performance of the Karma alloy thin film strain gauge was also investigated. As the annealing temperature increased, it was found that the resistivity of the thin films decreased, whereas the temperature coefficient of resistance (TCR) of the thin films increased. A Karma alloy thin film strain gauge was annealed at 200 °C, thereby obtaining a gauge factor of 1.7 and a corresponding TCR of 64.8 × 10-6 K-1. The prepared Karma alloy thin film strain gauge had a lower TCR than other strain gauges at room temperature. This result can provide a reference for the preparation and application of Karma alloy thin film strain gauges in specific scenarios. Reference | Related Articles | Metrics