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    Influence of COVID-19 on Manufacturing Industry and Corresponding Countermeasures from Supply Chain Perspective
    CAI Min (蔡敏), LUO Jianwen (骆建文)
    J Shanghai Jiaotong Univ Sci    2020, 25 (4): 409-416.   DOI: 10.1007/s12204-020-2206-z
    Abstract779)      PDF (211KB)(29)      
    It is critical for the recovery of manufacturing industry against COVID-19 by analyzing its impact
    from supply chain perspective and exploring corresponding countermeasures. Firstly, this paper studies the initial
    impact caused by worldwide spread of the coronavirus, such as production disruption of raw material and spare
    parts, unsatisfied market demand due to setbacks in logistics, increasing bankruptcy risk for small and mediumsized
    enterprises (SMEs), and demand fluctuation enlargement. Secondly, the aftershock of COVID-19 is analyzed.
    With the trend of regionalization and digitalization, two-step countermeasures are proposed to help the recovery
    of manufacturing industry within the pandemic and better prepare for the post-COVID-19 world from supply
    chain perspective.
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    Missile-Target Situation Assessment Model Based on Reinforcement Learning
    ZHANG Yun, Lü Runyan, CAI Yunze
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (5): 561-568.   DOI: 10.1007/s12204-020-2226-8
    Abstract523)      PDF (724KB)(26)      
    In situation assessment (SA) of missile versus target fighter, the traditional SA models generally
    have the characteristics of strong subjectivity and poor dynamic adaptability. This paper considers SA as an
    expectation of future returns and establishes a missile-target simulation battle model. The actor-critic (AC)
    algorithm in reinforcement learning (RL) is used to train the evaluation network, and a missile-target SA model
    is established in simulation battle training. Simulation and comparative experiments show that the model can
    effectively estimate the expected effect of missile attack under the current situation, and it provides an effective
    basis for missile attack decision.
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    Particle Swarm Optimization Based on Hybrid Kalman Filter and Particle Filter 
    PENG Pai, CHEN Cong , YANG Yongsheng
    J Shanghai Jiaotong Univ Sci    2020, 25 (6): 681-688.   DOI: 10.1007/s12204-020-2229-5
    Abstract511)      PDF (516KB)(11)      
    The combination of particle swarm and filters is a hot topic in the research of particle swarm optimization (PSO). The Kalman filter based PSO (K-PSO) algorithm is efficient, but it is prone to premature convergence. In this paper, a particle filter based PSO (P-PSO) algorithm is proposed, which is a fine search with fewer premature problems. Unfortunately, the P-PSO algorithm is of higher computational complexity. In order to avoid the premature problem and reduce the computational burden, a hybrid Kalman filter and particle filter based particle swarm optimization (HKP-PSO) algorithm is proposed. The HKP-PSO algorithm combines the fast convergence feature of K-PSO and the consistent convergence performance of P-PSO to avoid premature convergence as well as high computational complexity. The simulation results demonstrate that the proposed HKP-PSO algorithm can achieve better optimal solution than other six PSO related algorithms.

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    Multi-Objective Optimal Feedback Controls for Under-Actuated Dynamical System
    QIN Zhichang, XIN Ying, SUN Jianqiao
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (5): 545-552.   DOI: 10.1007/s12204-020-2211-2
    Abstract508)      PDF (1584KB)(24)      
     This paper presents a study of optimal control design for a single-inverted pendulum (SIP) system with
    the multi-objective particle swarm optimization (MOPSO) algorithm. The proportional derivative (PD) control
    algorithm is utilized to control the system. Since the SIP system is nonlinear and the output (the pendulum angle)
    cannot be directly controlled (it is under-actuated), the PD control gains are not tuned with classical approaches.
    In this work, the MOPSO method is used to obtain the best PD gains. The use of multi-objective optimization
    algorithm allows the control design of the system without the need of linearization, which is not provided by
    using classical methods. The multi-objective optimal control design of the nonlinear system involves four design
    parameters (PD gains) and six objective functions (time-domain performance indices). The Hausdorff distances of
    consecutive Pareto sets, obtained in the MOPSO iterations, are computed to check the convergence of the MOPSO
    algorithm. The MOPSO algorithm finds the Pareto set and the Pareto front efficiently. Numerical simulations
    and experiments of the rotary inverted pendulum system are done to verify this design technique. Numerical and
    experimental results show that the multi-objective optimal controls offer a wide range of choices including the
    ones that have comparable performance to the linear quadratic regulator (LQR) control.
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    Three-Dimensional Trajectory Tracking Control of Underactuated Autonomous Underwater Vehicles with Input Saturation
    HUANG Hantao, ZHOU Jingye, DI Qing, ZHOU Jiawei , LI Jiawang
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 470-477.   DOI: 10.1007/s12204-020-2195-y
    Abstract507)      PDF (310KB)(32)      
    This paper addresses a three-dimensional (3D) trajectory tracking problem of underactuated autonomous
    underwater vehicles (AUVs) subjected to input saturation and external disturbances. The proposed
    controller can achieve practical convergence of tracking errors for general reference trajectories, including persistently
    exciting (PE) time varying trajectories and fixed points. At first, a modified error state formulation
    is introduced to tackle the situation that desired velocities do not satisfy PE condition. Then, on the basis of
    the backstepping technique and a Nussbaum-type even function, a saturated controller is designed so that the
    tracking errors can converge to a bounded neighborhood of the origin. The stability analysis based on Lyapunov
    theory shows that the tracking errors are globally ultimately uniformly bounded. Finally, some simulation results
    illustrate the effectiveness and robustness of the proposed control strategy.
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    Fatigue Life Prediction for Flange Connecting Bolts of Wind Turbine Tower
    YU Zelin, SUN Pengwen, WANG Dong
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 526-530.   DOI: 10.1007/s12204-020-2173-4
    Abstract505)      PDF (1312KB)(19)      
    Flange joint part is the weak link of wind turbine tower. In view of the special structure, complex stress
    and easy failure of the connecting bolt of the wind turbine tower flange, the relationship between the external
    load of the tower section and the internal stress of the bolt is established by the finite element method, and the
    time series internal stress of the bolt is calculated by the Schmidt-Neuper algorithm. The S-N curve which is
    suitable for the connecting bolt material of the tower flange is selected by the GL2010 specification. On the basis
    of Miner’s fatigue cumulative damage theory and rain flow counting method, the fatigue strength of the whole
    ring bolt is roughly calculated, and the most dangerous part is determined. The axial symmetry model of screw
    connection is used for accurately calculating the fatigue cumulative damage of the bolt at the dangerous part.
    The results show that the fatigue life of the bolts in the most dangerous position can meet the requirements, the
    engineering algorithm has advantages in determining the dangerous part of the whole ring bolt, and the finite
    element method has high accuracy in predicting the fatigue life of the bolts in the dangerous part. The proposed
    method is feasible and effective in predicting the fatigue life of the flange joint bolts of the tower.
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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
    Abstract489)      PDF (86KB)(199)      
    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.
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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
    Abstract483)      PDF (917KB)(135)      
    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.

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    Coupling Mathematical Model of Marine Propulsion Shafting in Steady Operating State
    WEN Xiaofei, ZHOU Ruiping, YUAN Qiang, LEI Junsong
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 463-469.   DOI: 10.1007/s12204-020-2192-1
    Abstract473)      PDF (464KB)(18)      
    According to the analysis of the problems about the operation of marine propulsion shafting in steady
    state, the geometric and mechanical coupling relationships between marine propulsion shafting and oil film of
    bearings in two-dimensional space are established, and a coupling mathematical model of the marine propulsion
    shafting in steady operating state is proposed. Then the simulation of a real ship is carried out, and the variation
    laws of some special parameters such as bearing load and deflection are obtained. Finally, the results of simulation
    are verified by experimental data of a real ship, which can provide the mathematical model and analysis method
    for the research on the characteristics of ship propulsion shafting condition in steady state.
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    Effect of Wall Deformation on Dewatering-Induced Ground Surface Settlement
    NAI Kimsrorng, LI Mingguang, CHEN Jinjian
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 417-425.   DOI: 10.1007/s12204-020-2207-y
    Abstract469)      PDF (460KB)(17)      
     In practice, dewatering for pressure relief is commonly undertaken during ongoing excavation to secure
    bottom stability against basal upheaval. Simultaneously, through unloading, wall deflection is obviously observed.
    Noticing that both cause soil deformations, this research is to study the effect of wall deformation on dewateringinduced
    settlement. A coupled numerical analysis of finite-difference software is employed to model Shanghai
    soft soils under multi-aquifer-aquitard systems (MAASs) by analyzing the results in association with an empirical
    approach. Consequently, through gradual force reduction, shear strength at soil-wall interface is significantly
    diminished. As wall deformation increases instantaneously upon lower loading, wall surface becomes deformedly
    bending; this condition causes the challenge to workability of shear strength. Moreover, wall deformation caused
    by unloading affects dewatering-induced settlement substantially. Under smaller loading, large wall deflection
    is observed; soil plane of failure caused by both sliding and compression occurs along slip curve, with weaker
    shear-strength soils at rD = 0.4 and stronger shear-strength soils between rD = 0.4 and rD = 0.65, where rD is the
    distance from the wall that is normalized by the depth measured from ground surface. During dewatering, stronger
    soils tend to drag weaker soils upward to reduce large differential settlements caused by additional compression.
    Consequently, settlement becomes larger at rD = 0.4 and smaller at rD = 0.65. Remarkably, at rD > 2.3,
    both settlement curves that result from numerical analysis and empirical method show overlapping; this indicates
    that the unloading effect on dewatering-induced settlement at rD > 2.3 is insignificant. Furthermore, as wall
    reaches maximum allowable wall deflection by 67% applied force, additional compression caused by dewatering
    after loading remains smaller than that under 70% applied force, contributing to smaller dewatering-induced
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    How to Calculate Stormwater Management and Storage Capacity for Urban Green Space: Multidisciplinary Methods Used in Shanghai City
    YU Bingqin, GUO Jiankang, TIAN Shu, CHEN Yan, Lü Yongpeng, MO Zulan
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 426-433.   DOI: 10.1007/s12204-020-2189-9
    Abstract466)      PDF (3354KB)(14)      
     In order to relieve urban environmental problems due to stormwater runoff, approaches involving the
    planning of green space for sponge city construction were previously proposed. In this study, water retention
    characteristics of 168 green spaces are surveyed to develop estimates of stormwater retention in Shanghai City’s
    center, suburbs and outskirts. Multidisciplinary methods of community investigation, soil tests, artificial rainfall
    simulation experiments, and simulations in Autodesk storm and sanitary analysis (SSA) and storm water management
    model (SWMM) are used. The factors affecting the capacity of stormwater management are identified
    and used to calculate storage estimates. The relationships among rainfall interception capacity (RIC), runoff,
    soil water storage properties, and vegetative cover are analyzed, which can provide the theoretical foundation for
    the assessment of the water-holding capacity in urban green spaces. A criterion for the selection of low impact
    development (LID) techniques for the Shanghai area is developed on the basis of the data from this study.
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    Mechanism of MSWI Fly Ash Solidified by Microbe Cement
    RONG Hui, WEI Guanqi, QIAN Chunxiang, ZHANG Lei, ZHANG Ying, XU Rui
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 519-525.   DOI: 10.1007/s12204-020-2199-7
    Abstract459)      PDF (5919KB)(34)      
    Microbe cement, a new type of gelling material, has attracted wide attention due to the increasing
    awareness of environmental protection. In this paper, the microbe cement in solidifying municipal solid waste
    incineration (MSWI) fly ash is investigated and the effect of the microbial induction method in solidifying MSWI
    fly ash is compared with the traditional chemical reaction strategy by characterizing the resulted calcite and the
    solidification productions with electronic universal testing machine, X-ray diffractometer (XRD), Fourier transform
    infrared spectrometer (FTIR), scanning electron microscope (SEM) and atomic absorption spectrometer. The
    results show that the MSWI fly ash solidified by microbe cement has the highest compressive strength while that
    of the chemical CaCO3 products is the lowest. The XRD results show that a new hydration gelling substance
    (Ca2SiO4·0.30H2O) is generated in the MSWI fly ash products. The FTIR results show that the frequency of
    Si—O bonds and C—O bonds in the products solidified by microbe cement has shifted, while there is no change
    occurred in the chemical CaCO3 products. The SEM results show that the microstructure of the products solidified
    by microbe cement is denser than that of chemical CaCO3 products. The test results of heavy metals show that
    the microbe cement could reduce the leaching concentration of heavy metals in MSWI fly ash. Ultimately, the
    leaching concentration of Pb meets the standard requirements, while that of Cd is still slightly higher than the
    standard requirement.
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    Multi-Objective Structural Optimization of a Wind Turbine Tower
    ZHENG Yuqiao, ZHANG Lu, PAN Yongxiang, HE Zhe
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 538-544.   DOI: 10.1007/s12204-020-2190-3
    Abstract453)      PDF (342KB)(14)      
    The 2MW wind turbine tower is considered as the baseline configuration for structural optimization.
    The design variables consist of the thickness and height located at the top tower junction. The relationships
    between the design variables and the optimization objectives (mass, equivalent stress, top displacement and
    fatigue life) are mapped on the basis of uniform design and regression analysis. Subsequently, five solutions are
    developed by an algorithm, NSGA-III. According to their efficiency and applicability, the most suitable solution
    is found. This approach yields a decrease of 0.48% in the mass, a decrease of 54.48% in the equivalent stress and
    an increase of 8.14% in fatigue life, as compared with existing tower designs. An improved wind turbine tower is
    obtained for this practice.
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    Vibration of Axle Box from Wheel Diameter Difference in Vehicle
    CHENG Daolai, XU Lei, SUN Xiaojie
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 509-518.   DOI: 10.1007/s12204-020-2180-5
    Abstract450)      PDF (1006KB)(18)      
    The wheel diameter difference would worsen the dynamic performance and affect the safety of the
    rail vehicle. Therefore, it is necessary to detect wheel diameter difference while the train is operating. However,
    several existing detection methods can’t accurately detect and diagnose the wheel diameter difference under highspeed
    running environment. In this study, a new method of detecting wheel diameter difference was proposed
    for high speed rail vehicle. The wheel diameter difference would be diagnosed by the amplitude and frequency
    of vibration impact on the axle box. Firstly, the dynamic model with varying wheel diameters was established
    in SIMPACK, and LMA tread was used in high-speed rail vehicles. Then, the simulation results of rail vehicle
    dynamic performance were compared under different wheel diameter differences. After that, the relationship
    between axle box vibration and wheel diameter difference was used to demonstrate the feasibility of this detection
    technology. Finally, comparing and analyzing the simulation results of vibration obtained by matching treads
    with different wheel diameters, it shows that by increasing the wheel diameter difference, the longitudinal and
    lateral impacts on axle boxes increase asymmetrically, and the amplitude and the frequency become more evident.
    Therefore, this paper presents a technical scheme of online measuring wheel diameter difference by monitoring the
    vibration of the axle box.
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    Active Disturbance Rejection Controller Based Heading Control of Underwater Flight Vehicles
    ZHENG Tianhai, FENG Zhengping, ZHAO Shuo, PAN Wanjun
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 441-446.   DOI: 10.1007/s12204-020-2194-z
    Abstract450)      PDF (2251KB)(49)      
    The total disturbance estimated by the extended state observer (ESO) in active disturbance rejection
    controller (ADRC) is affected greatly by measurement noise when the control step is small in heading control
    of underwater flight vehicles (UFVs). In order to prevent rudder from high-frequency chattering caused by
    measurement noise, a tracking-differentiator (TD) is integrated to the ESO to develop an improved ADRC scheme.
    The improved ADRC suppresses the impact of sensor noise. Both the results of simulations and tank tests show
    the effectiveness of improved ADRC based heading control.
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    Adaptive Dual Wavelet Threshold Denoising Function Combined with Allan Variance for Tuning FOG-SINS Filter
    BESSAAD Nassim, BAO Qilian, SUN Shuodong, DU Yuding, LIU Lin, HASSAN Mahmood Ul
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 434-440.   DOI: 10.1007/s12204-020-2208-x
    Abstract434)      PDF (950KB)(18)      
     Allan variance (AV) stochastic process identification method for inertial sensors has successfully combined
    the wavelet transform denoising scheme. However, the latter usually employs a traditional hard threshold
    or soft threshold that presents some mathematical problems. An adaptive dual threshold for discrete wavelet
    transform (DWT) denoising function overcomes the disadvantages of traditional approaches. Assume that two
    thresholds for noise and signal and special fuzzy evaluation function for the signal with range between the two
    thresholds assure continuity and overcome previous difficulties. On the basis of AV, an application for strap-down
    inertial navigation system (SINS) stochastic model extraction assures more efficient tuning of the augmented 21-
    state improved exact modeling Kalman filter (IEMKF) states. The experimental results show that the proposed
    algorithm is superior in denoising performance. Furthermore, the improved filter estimation of navigation solution
    is better than that of conventional Kalman filter (CKF).
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    Assembly Information Model Based on Knowledge Graph
    CHEN Zhiyu, BAO Jinsong, ZHENG Xiaohu, LIU Tianyuan
    J Shanghai Jiaotong Univ Sci    2020, 25 (5): 578-588.   DOI: 10.1007/s12204-020-2179-y
    Abstract432)      PDF (1606KB)(21)      
    There are heterogeneous problems between the CAD model and the assembly process document. In
    the planning stage of assembly process, these heterogeneous problems can decrease the efficiency of information
    interaction. Based on knowledge graph, this paper proposes an assembly information model (KGAM) to integrate
    geometric information from CAD model, non-geometric information and semantic information from assembly
    process document. KGAM describes the integrated assembly process information as a knowledge graph in the
    form of “entity-relationship-entity” and “entity-attribute-value”, which can improve the efficiency of information
    interaction. Taking the trial assembly stage of a certain type of aero-engine compressor rotor component as an
    example, KGAM is used to get its assembly process knowledge graph. The trial data show the query and update
    rate of assembly attribute information is improved by more than once. And the query and update rate of assembly
    semantic information is improved by more than twice. In conclusion, KGAM can solve the heterogeneous problems
    between the CAD model and the assembly process document and improve the information interaction efficiency.
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    Supporting Earth Pressures for Foundation Excavation Considering Suction Stress of Soil
    LI Jingpei, CAO Xiaobing, LI Lin
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 486-494.   DOI: 10.1007/s12204-020-2187-y
    Abstract430)      PDF (379KB)(17)      
    The infiltration, evaporation and variation of the groundwater table have significant effects on the
    suction stress of the soils and the supporting earth pressures of the foundation excavation. The distribution
    of the suction stresses above the ground water table is derived under different fluxes at the ground surface,
    according to the soil-water characteristic parameters and the effective degree of saturation. In consideration of
    the cohesive stress formed from the soil suction stress and the relevant anti sliding effect, the calculation model
    of supporting earth pressures for foundation excavation is established by the variational limit equilibrium method
    under the steady flow condition. The evolution of the supporting earth pressures is studied in detail for foundation
    excavation under different fluxes at the ground surface. The effects of the soil-water characteristic parameters, the
    ground water table and the internal friction angle on the supporting earth pressures are discussed. The results
    show that the suction stress is reduced because of the infiltration, and thus the supporting earth pressure increases.
    The larger the air-entry pressures and the pore size are, the smaller the supporting earth pressures are. The higher
    the ground water table is, the larger the supporting earth pressures are. In order to reduce the construction risk,
    the effects of the suction stress and the evolution of the potential critical sliding surface should be considered
    during the calculation of the supporting earth pressures.
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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
    Abstract420)      PDF (1551KB)(121)      
    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.

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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
    Abstract420)      PDF (1040KB)(247)      
    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.
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    Sliding Mode Control of T-Shaped Pedestrian Channel
    CHANG Lu, SHAN Liang, LI Jun, DAI Yuewei
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 478-485.   DOI: 10.1007/s12204-020-2198-8
    Abstract418)      PDF (776KB)(18)      
    The study of pedestrian evacuation in channels with different structures is important among optimizing
    through efficiency, avoiding accidents and designing passageway. It is of significant reference to set up a specific
    model on account of the real traffic system and design an appropriate controller to apply on it. This paper
    establishes a macroscopic model for T-shaped channel with a number of controlled entrances basing on the law
    of mass conservation. Then, with the method of cascade, a kind of sliding mode controller is designed to achieve
    the control target of avoiding the blocking and maximizing the pedestrian flow of the whole model, the stability
    of the system is proved by the Lyapunov stability theory, and the boundary layer method is applied to restrain
    the chattering of the controller. Finally, simulation results show the efficiency of the sliding mode controller and
    the improvement brought by the boundary layer method.
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    Effects of Micro-Milling and Laser Engraving on Processing Quality and Implantation Mechanics of PEG-Dexamethasone Coated Neural Probe
    ZHOU Xuhui (周旭辉), ZHANG Wenguang (张文光), XIE Jie (谢颉)
    J Shanghai Jiaotong Univ Sci    2021, 26 (1): 1-9.   DOI: 10.1007/s12204-020-2243-7
    Abstract397)      PDF (1890KB)(52)      
     Compared with stiff silicon-based probes, flexible neural probes can alleviate biological inflammation and tissue rejection. A polyethylene glycol (PEG) coating can facilitate the insertion of flexible probes, and the fabrication methods have a significant impact on the dimensional accuracy and structural strength of the coating. In this study, a novel melting injection moulding method is used to process a PEG-dexamethasone (PEG-DEX) coating with high structural strength for a type of mesh-shaped photosensitive polyimide (PSPI) based neural probe. Combined with the digital image correlation (DIC) method, an in vitro test system with high accuracy is developed to evaluate the effects of the elastic modulus of the PEG component and two fabrication methods, i.e., computer-numerical-control (CNC) micro-milling and laser engraving, on the processing quality and implantation mechanics of a PEG-DEX coated probe. The results show that compared with laser engraving, CNC micro-milling can ensure high dimensional accuracy and sharpness for the composite coating, thus leading to small damage from implantation, whereas the elastic modulus of the composite coating has a limited effect on the implantation mechanics of the PEG-DEX coated probe.

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    Numerical Computation of a Mixed-Integer Optimal Control Problem Based on Quantum Annealing
    LIU Zhe, LI Shurong, GE Yulei
    J Shanghai Jiaotong Univ Sci    2020, 25 (5): 623-629.   DOI: 10.1007/s12204-020-2220-1
    Abstract396)      PDF (211KB)(15)      
    It is extremely challenging to solve the mixed-integer optimal control problems (MIOCPs) due to
    the complex computation in solving the integer decision variables. This paper presents a new method based
    on quantum annealing (QA) to solve MIOCP. The QA is a metaheuristic which applies quantum tunneling in
    the annealing process. It has a faster convergence speed in optimal-searching and is less likely to run into local
    minima. Hence, QA is applied to deal with this kind of optimization problems. First, MIOCP is transformed into
    a mixed-integer nonlinear programming (MINLP). Then, a method based on QA is adopted to solve the MINLP
    and acquire the optimal solution. At last, two benchmark examples including Lotka-Volterra type fishing problem
    and distillation column are presented and solved. The effectiveness of the methodology is verified by the acquired
    optimal schemes.
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    Data-Driven Fault Detection of Three-Tank System Applying MWAT-ICA
    LIU Mingguang, LIAO Yaxuan, LI Xiangshun
    J Shanghai Jiaotong Univ Sci    2020, 25 (5): 659-664.   DOI: 10.1007/s12204-020-2227-7
    Abstract396)      PDF (212KB)(18)      
    In order to improve monitoring performance of dynamic process, a moving window independent component
    analysis method with adaptive threshold (MWAT-ICA) is proposed. On-line fault detection can be realized
    by applying moving windows technique, as well as false alarm caused by fluctuation of data can be effectively
    avoided by adaptive threshold. The efficiency of the proposed approach is demonstrated with a three-tank system.
    The results show that the MWAT-ICA can not only detect the fault quickly, but also has a high fault detection
    rate and no false alarm rate under the transient behaviors of the three-water tank and the normal operation
    process. These results demonstrate the effectiveness of the method for fault detection on the three-tank system.
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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
    Abstract395)      PDF (2268KB)(161)      
    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.
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    Simulation Research on Operation of Union Purchase System in Navigation Simulator
    FAN hang, YANG Shenhua, SUO Yongfeng, ZHENG Minjie
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (5): 606-614.   DOI: 10.1007/s12204-020-2193-0
    Abstract385)      PDF (2104KB)(24)      
    Navigation is the only way to develop and utilize marine resources, while the promotion of seafarers’
    quality is the basic force of navigation, so navigation simulator plays an important role in modern navigation
    education. The simulation research on the operation of the union purchase is important to improve the special
    operation training of the actual cargo handling of the union purchase. On the basis of the Cartesian coordinate
    system transformation algorithm, the algorithm model of the union purchase operation is constructed. On the
    basis of three-dimensional (3D) rendering engine technology of open scene graph (OSG), the algorithm model
    of finding the space coordinates of the cargo point is established. The model of catenary equation is used to
    optimize the scene appearance of the cargo wire. By combination of QT channel signal mechanism and OSG, the
    simulation interaction of the union purchase operating system is realized. By acquiring the 3D coordinate values
    of each point, we fit the trajectories of each point in the operation and compare the trajectories. The results
    show that the model has high interactivity and small error. The comparison of the states of the cargo wire before
    and after optimization shows that the optimized wire is more realistic and the high fidelity meets the needs of
    operational training and simulation systems.
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    Collaborative Tracking Method in Multi-Camera System
    ZHOU Zhipeng, YIN Dong, DING Jinwen, LUO Yuhao, YUAN Mingyue, ZHU Chengfeng
    J Shanghai Jiaotong Univ Sci    2020, 25 (6): 802-810.   DOI: 10.1007/s12204-020-2188-x
    Abstract377)      PDF (2111KB)(7)      
    Visual tracking has been a popular task in computer vision in recent years, especially for long-term tracking. A novel object tracking framework is proposed in this paper. For surveillance cameras with overlapping areas, the target area is divided into several regions corresponding to each camera, and a simple re-matching method is used by matching the colors according to the segmented parts. For surveillance cameras without overlapping areas, a time estimation model is employed for continuously tracking objects in different fields of view (FoVs). A demonstration system for collaborative tracking in real time situation is realized finally. The experimental results show that compared with current popular algorithms, the proposed approach has good effect in accuracy and computation time for the application of continuously tracking the pedestrians.

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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
    Abstract375)      PDF (1198KB)(146)      
    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.

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    Leakage Model of Axial Clearance and Test of Scroll Compressors
    WANG Jianji, LIU Tao
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 531-537.   DOI: 10.1007/s12204-020-2163-6
    Abstract366)      PDF (8187KB)(20)      
     Leakage clearance plays an important role in guaranteeing high efficiency of scroll compressors. In view
    of the shortcomings of the existing leakage models of axial clearance of scroll compressors, a modified Fano flow
    model and a turbulence model are presented based on the flow characteristics of fluid in the leakage passage under
    actual working conditions. Firstly, according to the Fano flow energy equation and the turbulence theory, two kinds
    of leakage models, Fano flow model and turbulence model, of axial clearance are established. Then, the established
    models are verified through an experimental platform established to measure the axial clearance leakage in the
    working process of a scroll compressor, and the measured values are compared with the values obtained from the
    two theoretical models. Finally, the effect of such factors as pressure difference, clearance amount, spindle speed
    on the axial clearance leakage is analyzed. Results show that the two established models can precisely reflect the
    variation law of axial clearance leakage of scroll compressor under different working conditions. In particular, the
    Fano flow model is more suitable for predicting the clearance leakage when the spindle speed is low (less than
    3 500 r/min) and the clearance is small (less than 0.025 mm), whereas the turbulence model is suitable for high
    spindle speed (more than 3 500 r/min) and large clearance (more than 0.025 mm).
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    Lifetime Prediction of Wind Turbine Blade Based on Full-Scale Fatigue Testing  
    KOU Haixia, AN Zongwen, MA Qiang, GUO Xu
    J Shanghai Jiaotong Univ Sci    2020, 25 (6): 755-761.   DOI: 10.1007/s12204-020-2174-3
    Abstract360)      PDF (269KB)(7)      
     In order to predict the lifetime of products appropriately with long lifetime and high reliability, the accelerated degradation testing (ADT) has been proposed. Composite wind turbine blade is one of the most important components in wind turbine system. Its fatigue cycle is very long in practice. A full-scale fatigue testing is usually used to verify the design of a new blade. In general, the full-scale fatigue testing of blade is accelerated on the basis of the damage equivalent principle. During the full-scale fatigue testing, blade is subjected to higher testing load than normal operating conditions; consequently, the performance degradation of the blade is hastened over time. The full-scale fatigue testing of blade is regarded as a special ADT. According to the fatigue failure criterion, we choose blade stiffness as the characteristic quantity of the blade performance, and propose an accelerated model (AM) for blade on the basis of the theories of ADT. Then, degradation path of the blade stiffness is modeled by using Gamma process. Finally, the lifetime prediction of full-scale megawatt (MW) blade is conducted by combining the proposed AM and blade stiffness degradation model. The prediction results prove the reasonability and validity of this study. This can supply a new approach to predict the lifetime of the full-scale MW blade.

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    Stability and Numerical Analysis of a Standby System
    QIAO Xing, MA Dan, YAO Xuliang, FENG Baolin
    J Shanghai Jiaotong Univ Sci    2020, 25 (6): 769-778.   DOI: 10.1007/s12204-020-2217-9
    Abstract358)      PDF (260KB)(11)      
    A model for repairable standby parallel system consisting of two identical components with common cause failure (CCF) and human error is introduced in this article by a semigroup approach. The stability of the system is verified by the pure analysis technique, the co-final related theory and functional analysis method. It is discussed that four different reliability indices of the studied model are consistent with each other both analytically and numerically. The simulations and comparisons demonstrate the validity of the proposed technique.

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    Scaling Relation of the Scalar Diffusion in a Rotating Mixer
    SUN Na (孙娜), WANG Lipo (王利坡), LI Yuanbo (李渊博), LI Lin (李琳), QI Shuaipeng (齐帅鹏), SHEN Yongxing (沈泳星)
    J Shanghai Jiaotong Univ Sci    2021, 26 (2): 170-175.   DOI: 10.1007/s12204-021-2275-7
    Abstract356)      PDF (1495KB)(33)      
    Scalar mixing is under the joint control of convection and diffusion. The ratio of the dissipative scale of velocity field to that of the scalar field depends on the Schmidt number. In the high Schmidt number limit, the scalar scale is much smaller than that of the momentum, which then requires either special treatment or ad hoc models for the scalar quantity in numerical simulations. In order to avoid model uncertainty or unnecessary numerical complexity, the direct numerical simulation is performed for studying the scalar mixing process in a confined rotating mixer tank. It has been found that in the range of negligible numerical diffusivity,the characteristic scalar mixing time is inversely proportional to the scalar diffusivity. Analysis based on the dimensional argument justifies such scaling relation as well, from which the unaccepted computational time of the mixing process in the high Schmidt number limit can be efficiently determined, without the use of ad hoc models. This scaling idea is also of practical meaningfulness for other similar problems.
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    Identification and Control of Flexible Joint Robot Using Multi-Time-Scale Neural Network
    ZHENG Dongdong, LI Pengcheng, XIE Wenfang, LI Dan
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (5): 553-560.   DOI: 10.1007/s12204-020-2210-3
    Abstract355)      PDF (391KB)(28)      
    In this paper, a new identification and control scheme for the flexible joint robotic manipulator is
    proposed. Firstly, by defining some new state variables, the commonly used dynamic equations of the flexible joint
    robotic manipulators are transformed into the standard form of a singularly perturbed model. Subsequently, an
    optimal bounded ellipsoid algorithm based identification scheme using multi-time-scale neural network is proposed
    to identify the unknown system dynamic equations. Lastly, by using the singular perturbation theory, an indirect
    adaptive controller based on the identified model is proposed to control the system such that the joint angles can
    track the given reference signals. The closed-loop stability of the whole system is proved, and the effectiveness of
    the proposed schemes is verified by simulations.
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    New Approach for Information Security Evaluation and Management of IT Systems in Educational Institutions
    WANG Mingzheng, WANG Yijie, WANG Tianyu, HOU Linzao, LI Mian
    J Shanghai Jiaotong Univ Sci    2020, 25 (6): 689-699.   DOI: 10.1007/s12204-020-2231-y
    Abstract348)      PDF (233KB)(15)      
    Security evaluation and management has become increasingly important for Web-based information technology (IT) systems, especially for educational institutions. For the security evaluation and management of IT systems in educational institutions, determining the security level for a single IT system has been well developed. However, it is still difficult to evaluate the information security level of the entire educational institution considering multiple IT systems, because there might be too many different IT systems in one institution, educational institutions can be very different, and there is no standard model or method to provide a justifiable information security evaluation among different educational institutions considering their differences. In light of these difficulties,a security evaluation model of educational institutions’ IT systems (SEMEIS) is proposed in this work to facilitate the information security management for the educational institutions. Firstly, a simplified educational industry information system security level protection rating (EIISSLPR) with a new weight redistribution strategy for a single IT system is proposed by choosing important evaluation questions from EIISSLPR and redistributing the weights of these questions. Then for the entire educational institution, analytic hierarchy process (AHP) is used to redistribute the weights of multiple IT systems at different security levels. Considering the risk of possible network security vulnerabilities, a risk index is formulated by weighting different factors, normalized by a utility function, and calculated with the real data collected from the institutions under the evaluation. Finally,the information security performance of educational institutions is obtained as the final score from SEMEIS. The results show that SEMEIS can evaluate the security level of the education institutions practically and provide an efficient and effective management tool for the information security management.

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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
    Abstract348)      PDF (2668KB)(292)      
    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.

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    Fractional Fourier Transform Based M-ary Chirp Modulation
    SHA Jiajun, ZHENG Guoxin, YANG Liu
    J Shanghai Jiaotong Univ Sci    2020, 25 (6): 795-801.   DOI: 10.1007/s12204-020-2191-2
    Abstract343)      PDF (317KB)(9)      
    In this paper, a novel M-ary chirp modulation scheme is proposed on the basis of the energy concentration property of chirp signals in fractional domain. In the proposed scheme, chirp signals with different phases are multiplexed in the same time-frequency bandwidth through reverse chirp-rate to increase information rate. In addition, fractional filters based on fractional Fourier transform (FRFT) are designed to separate chirp signals of different chirp-rates in the receiver. Moreover, the theoretical performance of fractional filters and the error probability of M-ary chirp system are derived. Both theoretical analysis and simulation prove that the proposed scheme outperforms M-ary quadrature amplitude modulation (QAM) system in the anti-noise performance.

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    BFM: A Bus-Like Data Feedback Mechanism Between Graphics Processor and Host CPU
    DENG Junyong, JIANG Lin
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (5): 615-622.   DOI: 10.1007/s12204-020-2221-0
    Abstract343)      PDF (575KB)(16)      
    Graphics processors have received an increasing attention with the growing demand for gaming, video
    streaming, and many other applications. During the graphics rendering with OpenGL, host CPU needs the runtime
    attributes to move on to the next procedure of rendering, which covers almost all the function units of
    graphics pipeline. Current methods suffer from the memory capacity issues to hold the variables or huge amount
    of data passing paths which can cause congestion on the interface between graphics processor and host CPU. This
    paper refers to the operation principle of commuting bus, and proposes a bus-like data feedback mechanism (BFM)
    to traverse all the pipeline stages and collect the run-time status data or execution error of graphics rendering,
    then send them back to the host CPU. BFM can work in parallel with the graphics rendering logic. This method
    can complete the data feedback task easily with only 0.6% increase of resource utilization and has no negative
    impact on performance, which also obtains 1.3 times speed enhancement compared with a traditional approach.
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    Intrafascicular Vagal Activity Recording and Analysis Based on Carbon Nanotube Yarn Electrodes
    ARRANZ Javier, GUO Jinyao, YU Xiao, WANG Jiaojiao, CHAI Xinyu, WANG Jiguang, SUI Xiaohong
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 447-452.   DOI: 10.1007/s12204-020-2197-9
    Abstract340)      PDF (2418KB)(48)      
    The vagus nerve carries sensory information from multiple organs in the body. The recording of
    its activity and further processing is a key step for neuromodulation treatments. This paper presents a specific
    algorithm for the processing and discrimination of intrafascicular recordings from the vagus nerve using the
    novel carbon nanotube yarn electrodes. Up to four different neural waveforms were found, whose occurrence
    corresponded to distinct levels of anesthesia depth.
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    Data-Driven Predictive Maintenance Approach for Spinning Cyber-Physical Production System
    FAROOQ Basit, BAO Jinsong, LI Jie, LIU Tianyuan, YIN Shiyong
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (4): 453-462.   DOI: 10.1007/s12204-020-2178-z
    Abstract339)      PDF (1444KB)(26)      
    The fundamental process of predictive maintenance is prognostics and health management, and it
    is the tool resulting in the development of many algorithms to predict the remaining useful life of industrial
    equipment. A new data-driven predictive maintenance and an architectural impulse, based on a regularized deep
    neural network using predictive analytics, are proposed successfully for ring spinning technology. The paradigm
    shift in computational infrastructures enormously puts pressure on large-scale linear and non-linear automated
    assembly systems to eliminate and cut down unscheduled downtime and unexpected stoppages. The sensor
    network designed for the scheduling process comprises different critical components of the same spinning machine
    frames containing more than thousands of spindles attached to them. We established a genetic algorithm based
    on multi-sensor performance assessment and prediction procedure for the spinning system. Results show that it
    operates with a relatively less amount of training data sets but takes advantage of larger volumes of data. This
    integrated system aims to prognosticate abnormalities, disturbances, and failures by providing condition-based
    monitoring for each component, which makes it more accurate to locate the defined component failures in the
    current spinning spindles by using smart agents during the operations through the neural sensing network. A case
    study has provided to demonstrate the feasibility of the proposed predictive model for highly dynamic, high-speed
    textile spinning system through real-time data sensing and signal processing via the industrial Internet of Things.
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    Low Data Overlap Rate Graph-Based SLAM with Distributed Submap Strategy
    XIANG Jiawei, ZHANG Jinyi, WANG Bin, MA Yongbin
    Journal of Shanghai Jiao Tong University(Science)    2020, 25 (5): 650-658.   DOI: 10.1007/s12204-020-2201-4
    Abstract334)      PDF (1218KB)(24)      
     Simultaneous localization and mapping (SLAM) is widely used in many robot applications to acquire
    the unknown environment’s map and the robot’s location. Graph-based SLAM is demonstrated to be effective in
    large-scale scenarios, and it intuitively performs the SLAM as a pose graph. But because of the high data overlap
    rate, traditional graph-based SLAM is not efficient in some respects, such as real time performance and memory
    usage. To reduce data overlap rate, a graph-based SLAM with distributed submap strategy (DSS) is presented.
    In its front-end, submap based scan matching is processed and loop closing detection is conducted. Moreover in
    its back-end, pose graph is updated for global optimization and submap merging. From a series of experiments, it
    is demonstrated that graph-based SLAM with DSS reduces 51.79% data overlap rate, decreases 39.70% runtime
    and 24.60% memory usage. The advantages over other low overlap rate method is also proved in runtime, memory
    usage, accuracy and robustness performance.
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